On the public citation graph

Automated machine learning with interpretation: A systematic review of methodologies and applications in healthcare

0 signed · 251 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.2017.18152openalex-snapshot

Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes

inferredcites →https://doi.org/10.1002/acm2.13964openalex-snapshot

MS‐Net: Learning to assess the malignant status of a lung nodule by a radiologist and her peers

inferredcites →https://doi.org/10.1002/hbm.26399openalex-snapshot

An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1‐weighted images

inferredcites →https://doi.org/10.1002/med4.70openalex-snapshot

Human‐in‐the‐loop machine learning for healthcare: Current progress and future opportunities in electronic health records

inferredcites →https://doi.org/10.1002/mp.16053openalex-snapshot

Multi‐scale, domain knowledge‐guided attention + random forest: a two‐stage deep learning‐based multi‐scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images

inferredcites →https://doi.org/10.1007/s00330-022-08575-zopenalex-snapshot

A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from high-grade gliomas

inferredcites →https://doi.org/10.1007/s00330-022-09032-7openalex-snapshot

AI-assisted biparametric MRI surveillance of prostate cancer: feasibility study

inferredcites →https://doi.org/10.1007/s00330-023-09590-4openalex-snapshot

Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning

inferredcites →https://doi.org/10.1007/s00330-023-09704-yopenalex-snapshot

Neural network algorithm for detection of erosions and ankylosis on CT of the sacroiliac joints: multicentre development and validation of diagnostic accuracy

inferredcites →https://doi.org/10.1007/s00417-021-05544-yopenalex-snapshot

Evaluating an automated machine learning model that predicts visual acuity outcomes in patients with neovascular age-related macular degeneration

inferredcites →https://doi.org/10.1007/s00521-022-07258-6openalex-snapshot

Tuberculosis detection in chest radiograph using convolutional neural network architecture and explainable artificial intelligence

inferredcites →https://doi.org/10.1007/s10140-022-02099-1openalex-snapshot

Toward automated interpretable AAST grading for blunt splenic injury

inferredcites →https://doi.org/10.1007/s10916-018-1134-zopenalex-snapshot

A Systematic Mapping Study of Data Preparation in Heart Disease Knowledge Discovery

inferredcites →https://doi.org/10.1007/s11227-022-04631-zopenalex-snapshot

Explainable artificial intelligence approach in combating real-time surveillance of COVID19 pandemic from CT scan and X-ray images using ensemble model

inferredcites →https://doi.org/10.1007/s11263-021-01449-9openalex-snapshot

Development and Validation of an Unsupervised Feature Learning System for Leukocyte Characterization and Classification: A Multi-Hospital Study

inferredcites →https://doi.org/10.1007/s11517-022-02630-zopenalex-snapshot

GA-MADRID: design and validation of a machine learning tool for the diagnosis of Alzheimer’s disease and frontotemporal dementia using genetic algorithms

inferredcites →https://doi.org/10.1016/j.ajem.2024.01.037openalex-snapshot

Assessing the precision of artificial intelligence in ED triage decisions: Insights from a study with ChatGPT

inferredcites →https://doi.org/10.1016/j.artmed.2020.101822openalex-snapshot

Automated machine learning: Review of the state-of-the-art and opportunities for healthcare

inferredcites →https://doi.org/10.1016/j.artmed.2023.102587openalex-snapshot

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques

inferredcites →https://doi.org/10.1016/j.asoc.2022.109926openalex-snapshot

Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees

inferredcites →https://doi.org/10.1016/j.asoc.2023.110511openalex-snapshot

Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning

inferredcites →https://doi.org/10.1016/j.atherosclerosis.2020.11.008openalex-snapshot

Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study

inferredcites →https://doi.org/10.1016/j.bspc.2022.104429openalex-snapshot

Do not sleep on traditional machine learning

inferredcites →https://doi.org/10.1016/j.cmpb.2018.04.005openalex-snapshot

Deep learning for healthcare applications based on physiological signals: A review

inferredcites →https://doi.org/10.1016/j.cmpb.2021.106130openalex-snapshot

Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning architectures

inferredcites →https://doi.org/10.1016/j.cmpb.2023.107465openalex-snapshot

Explainable deep learning-based clinical decision support engine for MRI-based automated diagnosis of temporomandibular joint anterior disk displacement

inferredcites →https://doi.org/10.1016/j.cmpb.2023.107483openalex-snapshot

DeepMiCa: Automatic Segmentation and Classification of Breast Microcalcifications from Mammograms

inferredcites →https://doi.org/10.1016/j.cmpb.2023.107495openalex-snapshot

Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson’s disease

inferredcites →https://doi.org/10.1016/j.compbiomed.2007.03.006openalex-snapshot

Neuro-fuzzy classification of prostate cancer using NEFCLASS-J

inferredcites →https://doi.org/10.1016/j.compbiomed.2022.105550openalex-snapshot

Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals

inferredcites →https://doi.org/10.1016/j.compbiomed.2022.106043openalex-snapshot

Explainable, trustworthy, and ethical machine learning for healthcare: A survey

inferredcites →https://doi.org/10.1016/j.compbiomed.2022.106340openalex-snapshot

Automatic diagnosis and grading of Prostate Cancer with weakly supervised learning on whole slide images

inferredcites →https://doi.org/10.1016/j.compmedimag.2020.101701openalex-snapshot

Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy

inferredcites →https://doi.org/10.1016/j.compmedimag.2023.102261openalex-snapshot

Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach

inferredcites →https://doi.org/10.1016/j.ejrad.2019.03.015openalex-snapshot

Prediction of molecular subtypes of breast cancer using BI-RADS features based on a “white box” machine learning approach in a multi-modal imaging setting

inferredcites →https://doi.org/10.1016/j.eswa.2022.118398openalex-snapshot

Automated localization and severity period prediction of myocardial infarction with clinical interpretability based on deep learning and knowledge graph

inferredcites →https://doi.org/10.1016/j.fss.2011.09.009openalex-snapshot

Fuzzy criteria for feature selection

inferredcites →https://doi.org/10.1016/j.future.2020.03.008openalex-snapshot

Transformer fault diagnosis method using IoT based monitoring system and ensemble machine learning

inferredcites →https://doi.org/10.1016/j.future.2022.02.021openalex-snapshot

Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance

inferredcites →https://doi.org/10.1016/j.ijmedinf.2018.03.013openalex-snapshot

Concurrence of big data analytics and healthcare: A systematic review

inferredcites →https://doi.org/10.1016/j.ijmedinf.2019.05.015openalex-snapshot

Interpretable deep learning to map diagnostic texts to ICD-10 codes

inferredcites →https://doi.org/10.1016/j.ijmedinf.2021.104543openalex-snapshot

Automated ICD coding for primary diagnosis via clinically interpretable machine learning

inferredcites →https://doi.org/10.1016/j.jbi.2018.02.011openalex-snapshot

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text

inferredcites →https://doi.org/10.1016/j.jbi.2021.103728openalex-snapshot

Explainable automated coding of clinical notes using hierarchical label-wise attention networks and label embedding initialisation

inferredcites →https://doi.org/10.1016/j.jbi.2021.103746openalex-snapshot

Automatic phenotyping of electronical health record: PheVis algorithm

inferredcites →https://doi.org/10.1016/j.jbi.2021.103959openalex-snapshot

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data

inferredcites →https://doi.org/10.1016/j.jbi.2021.103980openalex-snapshot

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

inferredcites →https://doi.org/10.1016/j.jbi.2021.103982openalex-snapshot

AMMU: A survey of transformer-based biomedical pretrained language models

inferredcites →https://doi.org/10.1016/j.jbi.2022.104072openalex-snapshot

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data

inferredcites →https://doi.org/10.1016/j.jbi.2023.104485openalex-snapshot

FedScore: A privacy-preserving framework for federated scoring system development

inferredcites →https://doi.org/10.1016/j.knosys.2020.106622openalex-snapshot

AutoML: A survey of the state-of-the-art

inferredcites →https://doi.org/10.1016/j.media.2017.07.005openalex-snapshot

A survey on deep learning in medical image analysis

inferredcites →https://doi.org/10.1016/j.media.2017.12.009openalex-snapshot

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation

inferredcites →https://doi.org/10.1016/j.media.2020.101942openalex-snapshot

Automated interpretation of congenital heart disease from multi-view echocardiograms

inferredcites →https://doi.org/10.1016/j.media.2021.102145openalex-snapshot

APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation

inferredcites →https://doi.org/10.1016/j.neucom.2010.02.016openalex-snapshot

Rule extraction from support vector machines: A review

inferredcites →https://doi.org/10.1016/j.neucom.2021.04.044openalex-snapshot

Attention-based full slice brain CT image diagnosis with explanations

inferredcites →https://doi.org/10.1016/j.patcog.2021.108071openalex-snapshot

Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images

inferredcites →https://doi.org/10.1016/j.patcog.2022.108826openalex-snapshot

Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images

inferredcites →https://doi.org/10.1016/j.patter.2022.100493openalex-snapshot

Human-centered explainability for life sciences, healthcare, and medical informatics

inferredcites →https://doi.org/10.1016/j.pscychresns.2023.111696openalex-snapshot

Can diffusion tensor imaging have a diagnostic utility to differentiate early-onset forms of bipolar disorder and schizophrenia: A neuroimaging study with explainable machine learning algorithms

inferredcites →https://doi.org/10.1016/j.resuscitation.2019.01.015openalex-snapshot

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

inferredcites →https://doi.org/10.1016/j.xpro.2023.102302openalex-snapshot

A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes

inferredcites →https://doi.org/10.1016/s2589-7500(19)30108-6openalex-snapshot

Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study

inferredcites →https://doi.org/10.1017/s1431927619001442openalex-snapshot

ImageJ for the Next Generation of Scientific Image Data

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1038/nrg3920openalex-snapshot

Machine learning applications in genetics and genomics

inferredcites →https://doi.org/10.1038/s41467-019-13647-8openalex-snapshot

Automated acquisition of explainable knowledge from unannotated histopathology images

inferredcites →https://doi.org/10.1038/s41551-020-00626-4openalex-snapshot

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre

inferredcites →https://doi.org/10.1038/s41551-022-00898-yopenalex-snapshot

Shifting machine learning for healthcare from development to deployment and from models to data

inferredcites →https://doi.org/10.1038/s41551-023-01049-7openalex-snapshot

Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging

inferredcites →https://doi.org/10.1038/s41568-021-00408-3openalex-snapshot

Harnessing multimodal data integration to advance precision oncology

inferredcites →https://doi.org/10.1038/s41586-023-05881-4openalex-snapshot

Foundation models for generalist medical artificial intelligence

inferredcites →https://doi.org/10.1038/s41598-019-53925-5openalex-snapshot

Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance

inferredcites →https://doi.org/10.1038/s41746-019-0208-8openalex-snapshot

Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation

inferredcites →https://doi.org/10.1038/s41746-023-00838-3openalex-snapshot

DeepBreath—automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

inferredcites →https://doi.org/10.1038/s42256-021-00353-8openalex-snapshot

Machine learning to guide the use of adjuvant therapies for breast cancer

inferredcites →https://doi.org/10.1038/s42256-021-00404-0openalex-snapshot

Machine intelligence enabled radiomics

inferredcites →https://doi.org/10.1038/s42256-024-00807-9openalex-snapshot

Foundation model for cancer imaging biomarkers

inferredcites →https://doi.org/10.1038/s43856-021-00013-3openalex-snapshot

Determining breast cancer biomarker status and associated morphological features using deep learning

inferredcites →https://doi.org/10.1038/sdata.2016.35openalex-snapshot

MIMIC-III, a freely accessible critical care database

inferredcites →https://doi.org/10.1080/09332480.2020.1726112openalex-snapshot

The Importance of Data Cleaning: Three Visualization Examples

inferredcites →https://doi.org/10.1093/bib/bbab060openalex-snapshot

Explainability in transformer models for functional genomics

inferredcites →https://doi.org/10.1093/bib/bbab577openalex-snapshot

Capturing large genomic contexts for accurately predicting enhancer-promoter interactions

inferredcites →https://doi.org/10.1093/bib/bbx165openalex-snapshot

BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches

inferredcites →https://doi.org/10.1093/bioinformatics/btz339openalex-snapshot

Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities

inferredcites →https://doi.org/10.1093/bioinformatics/btz470openalex-snapshot

Scaling tree-based automated machine learning to biomedical big data with a feature set selector

inferredcites →https://doi.org/10.1093/database/baaa050openalex-snapshot

mAML: an automated machine learning pipeline with a microbiome repository for human disease classification

inferredcites →https://doi.org/10.1093/eurheartj/ehac617openalex-snapshot

Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy

inferredcites →https://doi.org/10.1093/jamia/ocaa053openalex-snapshot

Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

inferredcites →https://doi.org/10.1093/jamia/ocaa268openalex-snapshot

Trust and medical AI: the challenges we face and the expertise needed to overcome them

inferredcites →https://doi.org/10.1093/jamia/ocw135openalex-snapshot

Surrogate-assisted feature extraction for high-throughput phenotyping

inferredcites →https://doi.org/10.1093/jamiaopen/ooab015openalex-snapshot

Comparison and interpretability of machine learning models to predict severity of chest injury

inferredcites →https://doi.org/10.1097/mcg.0000000000001909openalex-snapshot

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis

inferredcites →https://doi.org/10.1098/rsos.220440openalex-snapshot

Forecasting the publication and citation outcomes of COVID-19 preprints

inferredcites →https://doi.org/10.1109/access.2018.2868098openalex-snapshot

Oriented Feature Selection SVM Applied to Cancer Prediction in Precision Medicine

inferredcites →https://doi.org/10.1109/access.2020.3032683openalex-snapshot

Testing the Generalizability of an Automated Method for Explaining Machine Learning Predictions on Asthma Patients’ Asthma Hospital Visits to an Academic Healthcare System

inferredcites →https://doi.org/10.1109/access.2023.3238969openalex-snapshot

Non-Invasive Assessment of Lung Water Content Using Chest Patch RF Sensors: A Computer Study Using NIH Patients CT Scan Database and AI Classification Algorithms

inferredcites →https://doi.org/10.1109/ijcnn.2004.1381025openalex-snapshot

2004 IEEE International Joint Conference on Neural Networks

inferredcites →https://doi.org/10.1109/jbhi.2020.3005769openalex-snapshot

Extracting Cause of Death From Verbal Autopsy With Deep Learning Interpretable Methods

inferredcites →https://doi.org/10.1109/jbhi.2022.3230061openalex-snapshot

Functional Age Estimation Through Neonatal Motion Characterization Using Continuous Video Recordings

inferredcites →https://doi.org/10.1109/jbhi.2023.3279340openalex-snapshot

Explanations as a New Metric for Feature Selection: A Systematic Approach

inferredcites →https://doi.org/10.1109/jbhi.2023.3299339openalex-snapshot

An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence

inferredcites →https://doi.org/10.1109/jproc.2015.2494198openalex-snapshot

Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets

inferredcites →https://doi.org/10.1109/jtehm.2021.3098173openalex-snapshot

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure

inferredcites →https://doi.org/10.1109/mcg.2022.3199727openalex-snapshot

SUBPLEX: A Visual Analytics Approach to Understand Local Model Explanations at the Subpopulation Level

inferredcites →https://doi.org/10.1109/mci.2012.2200770openalex-snapshot

2013 IEEE International Conference on Fuzzy Systems

inferredcites →https://doi.org/10.1109/rbme.2022.3185953openalex-snapshot

Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review

inferredcites →https://doi.org/10.1109/tcyb.2021.3052813openalex-snapshot

Deep-Learning-Based Automatic Selection of Fewest Channels for Brain–Machine Interfaces

inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot

Nearest neighbor pattern classification

inferredcites →https://doi.org/10.1109/tmi.2022.3156906openalex-snapshot

DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity

inferredcites →https://doi.org/10.1109/tnnls.2020.3027314openalex-snapshot

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

inferredcites →https://doi.org/10.1109/tnnls.2023.3346992openalex-snapshot

Approximate Policy Iteration With Deep Minimax Average Bellman Error Minimization

inferredcites →https://doi.org/10.1109/tnsre.2021.3138185openalex-snapshot

A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

inferredcites →https://doi.org/10.1109/tpami.2019.2918284openalex-snapshot

Convolutional Networks with Dense Connectivity

inferredcites →https://doi.org/10.1109/tpami.2021.3055564openalex-snapshot

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks

inferredcites →https://doi.org/10.1109/tpami.2022.3152247openalex-snapshot

A Survey on Vision Transformer

inferredcites →https://doi.org/10.1111/coin.12410openalex-snapshot

Interpretability in healthcare: A comparative study of local machine learning interpretability techniques

inferredcites →https://doi.org/10.1111/j.1467-9868.2005.00503.xopenalex-snapshot

Regularization and Variable Selection Via the Elastic Net

inferredcites →https://doi.org/10.1117/1.jmi.9.4.044502openalex-snapshot

Automated vascular analysis of breast thermograms with interpretable features

inferredcites →https://doi.org/10.1126/sciadv.abi8020openalex-snapshot

Predicting risk of sudden cardiac death in patients with cardiac sarcoidosis using multimodality imaging and personalized heart modeling in a multivariable classifier

inferredcites →https://doi.org/10.1128/msystems.00230-19openalex-snapshot

Interpretable Log Contrasts for the Classification of Health Biomarkers: a New Approach to Balance Selection

inferredcites →https://doi.org/10.1136/bmjhci-2021-100519openalex-snapshot

Clinical utility of automatic phenotype annotation in unstructured clinical notes: intensive care unit use

inferredcites →https://doi.org/10.1142/s0129065723500466openalex-snapshot

A Class-Imbalance Aware and Explainable Spatio-Temporal Graph Attention Network for Neonatal Seizure Detection

inferredcites →https://doi.org/10.1145/3219819.3219963openalex-snapshot

Deep Adversarial Learning for Multi-Modality Missing Data Completion

inferredcites →https://doi.org/10.1145/3359786openalex-snapshot

Techniques for interpretable machine learning

inferredcites →https://doi.org/10.1145/3469841openalex-snapshot

An Explainable Deep Learning Ensemble Model for Robust Diagnosis of Diabetic Retinopathy Grading

inferredcites →https://doi.org/10.1161/circimaging.117.005614openalex-snapshot

Machine Learning Approaches in Cardiovascular Imaging

inferredcites →https://doi.org/10.1161/circoutcomes.118.005289openalex-snapshot

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery

inferredcites →https://doi.org/10.1186/gb-2006-7-10-r100openalex-snapshot

CellProfiler: image analysis software for identifying and quantifying cell phenotypes

inferredcites →https://doi.org/10.1186/s12859-018-2205-3openalex-snapshot

Taxonomy-aware feature engineering for microbiome classification

inferredcites →https://doi.org/10.1186/s12859-021-03961-8openalex-snapshot

Tremor assessment using smartphone sensor data and fuzzy reasoning

inferredcites →https://doi.org/10.1186/s12911-020-01185-zopenalex-snapshot

Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches

inferredcites →https://doi.org/10.1186/s12911-021-01721-5openalex-snapshot

Interpretable CNN for ischemic stroke subtype classification with active model adaptation

inferredcites →https://doi.org/10.1186/s12911-022-01976-6openalex-snapshot

Diagnosis of cardiac abnormalities based on phonocardiogram using a novel fuzzy matching feature extraction method

inferredcites →https://doi.org/10.1186/s40644-023-00594-3openalex-snapshot

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot

Greedy function approximation: A gradient boosting machine.

inferredcites →https://doi.org/10.1308/003588406x130615openalex-snapshot

The Value of Modified Early Warning Score (MEWS) in Surgical In-Patients: A Prospective Observational Study

inferredcites →https://doi.org/10.1371/journal.pmed.1002701openalex-snapshot

Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study

inferredcites →https://doi.org/10.1371/journal.pone.0178378openalex-snapshot

Does expert knowledge improve automatic probabilistic classification of gait joint motion patterns in children with cerebral palsy?

inferredcites →https://doi.org/10.1371/journal.pone.0203007openalex-snapshot

Genomic region detection via Spatial Convex Clustering

inferredcites →https://doi.org/10.1371/journal.pone.0265254openalex-snapshot

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

inferredcites →https://doi.org/10.1371/journal.pone.0283587openalex-snapshot

SimpleMind: An open-source software environment that adds thinking to deep neural networks

inferredcites →https://doi.org/10.1371/journal.pone.0289613openalex-snapshot

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

inferredcites →https://doi.org/10.1609/aaai.v31i1.10871openalex-snapshot

Multilinear Regression for Embedded Feature Selection with Application to fMRI Analysis

inferredcites →https://doi.org/10.1609/aaai.v32i1.11678openalex-snapshot

Feature Engineering for Predictive Modeling Using Reinforcement Learning

inferredcites →https://doi.org/10.1609/aaai.v32i1.11815openalex-snapshot

Automatic Segmentation of Data Sequences

inferredcites →https://doi.org/10.1609/aaai.v33i01.33014854openalex-snapshot

Congestion Graphs for Automated Time Predictions

inferredcites →https://doi.org/10.1609/aaai.v33i01.33016666openalex-snapshot

Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation

inferredcites →https://doi.org/10.1609/aaai.v34i05.6331openalex-snapshot

ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

inferredcites →https://doi.org/10.1609/aaai.v35i6.16614openalex-snapshot

Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans

inferredcites →https://doi.org/10.1613/jair.1.11854openalex-snapshot

Benchmark and Survey of Automated Machine Learning Frameworks

inferredcites →https://doi.org/10.1613/jair.1.12228openalex-snapshot

A Survey on the Explainability of Supervised Machine Learning

inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot

SMOTE: Synthetic Minority Over-sampling Technique

inferredcites →https://doi.org/10.21037/jeccm.2018.01.10openalex-snapshot

Clinical scores for risk stratification of chest pain patients in the emergency department: an updated systematic review

inferredcites →https://doi.org/10.21037/jmai-23-106openalex-snapshot

Applying large language model artificial intelligence for retina International Classification of Diseases (ICD) coding

inferredcites →https://doi.org/10.2140/pjm.1955.5.807openalex-snapshot

Note on non-cooperative convex game

inferredcites →https://doi.org/10.2174/1386207319666160414105217openalex-snapshot

Decision Trees for Continuous Data and Conditional Mutual Information as a Criterion for Splitting Instances

inferredcites →https://doi.org/10.2196/21798openalex-snapshot

AutoScore: A Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records

inferredcites →https://doi.org/10.2196/23458openalex-snapshot

Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study

inferredcites →https://doi.org/10.2196/24153openalex-snapshot

Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis

inferredcites →https://doi.org/10.2196/33960openalex-snapshot

Factors Influencing Clinician Trust in Predictive Clinical Decision Support Systems for In-Hospital Deterioration: Qualitative Descriptive Study

inferredcites →https://doi.org/10.24963/ijcai.2017openalex-snapshot

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

inferredcites →https://doi.org/10.24963/ijcai.2020openalex-snapshot

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

inferredcites →https://doi.org/10.25046/aj050558openalex-snapshot

Interpretation of Machine Learning Models for Medical Diagnosis

inferredcites →https://doi.org/10.3346/jkms.2021.36.e46openalex-snapshot

Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective

inferredcites →https://doi.org/10.3389/fcimb.2022.886935openalex-snapshot

Automated Machine Learning for the Early Prediction of the Severity of Acute Pancreatitis in Hospitals

inferredcites →https://doi.org/10.3389/fmolb.2022.1086047openalex-snapshot

Deep learning based CT images automatic analysis model for active/non-active pulmonary tuberculosis differential diagnosis

inferredcites →https://doi.org/10.3389/fncom.2021.674028openalex-snapshot

Accurate Prediction of Children's ADHD Severity Using Family Burden Information: A Neural Lasso Approach

inferredcites →https://doi.org/10.3389/fpubh.2022.1019168openalex-snapshot

Machine learning approaches for prediction of early death among lung cancer patients with bone metastases using routine clinical characteristics: An analysis of 19,887 patients

inferredcites →https://doi.org/10.3390/cancers15051492openalex-snapshot

Adaptive Aquila Optimizer with Explainable Artificial Intelligence-Enabled Cancer Diagnosis on Medical Imaging

inferredcites →https://doi.org/10.3390/diagnostics11030528openalex-snapshot

Conventional Machine Learning versus Deep Learning for Magnification Dependent Histopathological Breast Cancer Image Classification: A Comparative Study with Visual Explanation

inferredcites →https://doi.org/10.3390/diagnostics12061482openalex-snapshot

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

inferredcites →https://doi.org/10.3390/diagnostics12092132openalex-snapshot

Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans

inferredcites →https://doi.org/10.3390/diagnostics13050859openalex-snapshot

Attention Deep Feature Extraction from Brain MRIs in Explainable Mode: DGXAINet

inferredcites →https://doi.org/10.3390/ijerph192215110openalex-snapshot

A Novel Epilepsy Detection Method Based on Feature Extraction by Deep Autoencoder on EEG Signal

inferredcites →https://doi.org/10.3390/ijms23137132openalex-snapshot

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

inferredcites →https://doi.org/10.3390/jcdd9120468openalex-snapshot

Prognostic Value of Combined Radiomic Features from Follow-Up DWI and T2-FLAIR in Acute Ischemic Stroke

inferredcites →https://doi.org/10.3390/jcm11216264openalex-snapshot

Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury

inferredcites →https://doi.org/10.3390/jpm12111930openalex-snapshot

Automated Machine Learning in Predicting 30-Day Mortality in Patients with Non-Cholestatic Cirrhosis

inferredcites →https://doi.org/10.3390/math8050770openalex-snapshot

Towards Personalized Diagnosis of Glioblastoma in Fluid-Attenuated Inversion Recovery (FLAIR) by Topological Interpretable Machine Learning

inferredcites →https://doi.org/10.3390/medicina58081090openalex-snapshot

Multi-Modal Brain Tumor Detection Using Deep Neural Network and Multiclass SVM

inferredcites →https://doi.org/10.3390/s21134331openalex-snapshot

Learning Explainable Time-Morphology Patterns for Automatic Arrhythmia Classification from Short Single-Lead ECGs

inferredcites →https://doi.org/10.34067/kid.0005102021openalex-snapshot

Explainable Biomarkers for Automated Glomerular and Patient-Level Disease Classification

inferredcites →https://doi.org/10.48550/arxiv.1609.06570openalex-snapshot

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning

inferredcites →https://doi.org/10.48550/arxiv.1810.13306openalex-snapshot

Automated Machine Learning: From Principles to Practices

inferredcites →https://doi.org/10.52202/068431-1613openalex-snapshot

Large Language Models Are Zero-Shot Reasoners

inferredcites →https://doi.org/10.5430/air.v2n3p45openalex-snapshot

An interpretable classifier for detection of cardiac arrhythmias by using the fuzzy decision tree

inferredcites →https://doi.org/10.7326/0003-4819-151-4-200908180-00136openalex-snapshot

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

inferredcites →https://doi.org/10.7717/peerj-cs.150openalex-snapshot

Interval Coded Scoring: a toolbox for interpretable scoring systems

inferredcites →https://doi.org/10.7906/indecs.15.3.4openalex-snapshot

Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/cpz1.70463openalex-snapshot

Dataset Readiness Assessment With Large Language Model (DRAFT–LLM): A Multi‐Axis Audit Guided by LLM

inferred← citeshttps://doi.org/10.1002/hcs2.114openalex-snapshot

Toward real‐world deployment of machine learning for health care: External validation, continual monitoring, and randomized clinical trials

inferred← citeshttps://doi.org/10.1002/hcs2.119openalex-snapshot

Leveraging anatomical constraints with uncertainty for pneumothorax segmentation

inferred← citeshttps://doi.org/10.1002/hcs2.70009openalex-snapshot

Rethinking Domain‐Specific Pretraining by Supervised or Self‐Supervised Learning for Chest Radiograph Classification: A Comparative Study Against ImageNet Counterparts in Cold‐Start Active Learning

inferred← citeshttps://doi.org/10.1002/ird3.113openalex-snapshot

Anatomic Boundary‐Aware Explanation for Convolutional Neural Networks in Diagnostic Radiology

inferred← citeshttps://doi.org/10.1002/ird3.115openalex-snapshot

Natural Language Processing for Chest X‐Ray Reports in the Transformer Era: BERT‐Like Encoders for Comprehension and GPT‐Like Decoders for Generation

inferred← citeshttps://doi.org/10.1002/med4.70000openalex-snapshot

Agentic Large Language Models for Healthcare: Current Progress and Future Opportunities

inferred← citeshttps://doi.org/10.1002/med4.70001openalex-snapshot

Overcoming Computational Resource Limitations in Deep Learning for Healthcare: Strategies Targeting Data, Model, and Computing

inferred← citeshttps://doi.org/10.1002/med4.70002openalex-snapshot

Toward the Comprehensive Evaluation of Medical Text Generation by Large Language Models: Programmatic Metrics, Human Assessment, and Large Language Models Judgment

inferred← citeshttps://doi.org/10.1002/med4.70030openalex-snapshot

A Bibliometric Analysis of Botulinum Toxin Type A in the Treatment of Lower Urinary Tract Dysfunction: Current Research Trends and Perspectives

inferred← citeshttps://doi.org/10.1002/med4.70032openalex-snapshot

The Burden and Trends of Soft Tissue and Extraosseous Sarcomas in China: An Observational Study From 1990 to 2021

inferred← citeshttps://doi.org/10.1002/med4.70064openalex-snapshot

GMMAS: Glioma Multiparametric MRI Analysis System for Fully‐Automated Layered Tumor Diagnosis and Prognostic Evaluation

inferred← citeshttps://doi.org/10.1002/med4.70082openalex-snapshot

AI‐Enabled Cardiac Rehabilitation for Patients With Heart Failure After Myocardial Infarction: Current Status and Future Prospects

inferred← citeshttps://doi.org/10.1002/med4.83openalex-snapshot

Clinical decision making: Evolving from the hypothetico‐deductive model to knowledge‐enhanced machine learning

inferred← citeshttps://doi.org/10.1007/978-3-032-04403-7_26openalex-snapshot

AutoML: A Tertiary Study of Phases, Methods, Tools, and Frameworks

inferred← citeshttps://doi.org/10.1007/978-3-032-32357-6_15openalex-snapshot

Verification of LTL Properties on Neural Networks for Chemical Process Monitoring

inferred← citeshttps://doi.org/10.1007/s00210-025-04884-4openalex-snapshot

Innovative immunotherapy approaches: harnessing synergy of dual checkpoint blockade in oncology

inferred← citeshttps://doi.org/10.1007/s10557-025-07683-4openalex-snapshot

Effect of Verapamil on Blood Glucose in Type 1 and Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

inferred← citeshttps://doi.org/10.1007/s11042-026-21942-yopenalex-snapshot

xAutoGA: an automated deep learning software to educate users

inferred← citeshttps://doi.org/10.1007/s12519-025-01007-0openalex-snapshot

Guidelines for clean intermittent catheterization in children

inferred← citeshttps://doi.org/10.1007/s12539-025-00795-3openalex-snapshot

SSLCNV: A Semi-supervised Learning Framework for Accurate Copy Number Variation Detection

inferred← citeshttps://doi.org/10.1016/b978-0-443-44915-4.00002-2openalex-snapshot

AI/ML applications in medical imaging

inferred← citeshttps://doi.org/10.1016/j.artmed.2025.103302openalex-snapshot

Automated Machine Learning in medical research: A systematic literature mapping study

inferred← citeshttps://doi.org/10.1016/j.bbcan.2026.189685openalex-snapshot

Nano meets CAR-T: A new era in cancer immunotherapy

inferred← citeshttps://doi.org/10.1016/j.ibmed.2026.100427openalex-snapshot

Medical data types in machine learning and their challenges: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.identj.2026.109797openalex-snapshot

No-Code and Low-Code Artificial Intelligence in Healthcare Imaging: A Scoping Review

inferred← citeshttps://doi.org/10.1016/j.patter.2025.101314openalex-snapshot

The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning

inferred← citeshttps://doi.org/10.1016/j.radonc.2025.111180openalex-snapshot

An intelligent postoperative management system for glioblastoma integrating automated segmentation, risk stratification, and recurrence spatial mapping

inferred← citeshttps://doi.org/10.1097/md.0000000000048671openalex-snapshot

Development and external validation of a malnutrition risk prediction model for elderly patients with stable chronic obstructive pulmonary disease using automated machine learning

inferred← citeshttps://doi.org/10.1101/2025.08.29.25333768openalex-snapshot

Leveraging Foundation Models in Maternal and Child Health: A Systematic Review

inferred← citeshttps://doi.org/10.1101/2025.09.27.25336784openalex-snapshot

Development and multicenter external validation of A Data-Driven Scoring System for Early and Rapid Identification of Sepsis in Emergency Departments

inferred← citeshttps://doi.org/10.1109/access.2025.3599828openalex-snapshot

Enhancing Sleep Stage Classification With Single Channel EEG: Feature Extraction and Random Forest-XGBoost Model

inferred← citeshttps://doi.org/10.1109/cins67018.2025.11411969openalex-snapshot

Automated Machine Learning (AutoML) for Scalable AI Solutions

inferred← citeshttps://doi.org/10.1109/icuis67429.2025.11380636openalex-snapshot

Enhancing Bone Marrow Diagnosis using Deep Learning Architectures

inferred← citeshttps://doi.org/10.1109/nnice68970.2026.11466210openalex-snapshot

Joint Optimization and Leakage-Proof Strategies for Imbalanced Data

inferred← citeshttps://doi.org/10.1111/cpr.70263openalex-snapshot

Integrated Engineering of CAR ‐T Cells for Solid Tumours

inferred← citeshttps://doi.org/10.1186/s12871-026-03620-6openalex-snapshot

Random forest-based prediction of early postoperative pain after pelvic organ prolapse surgery under standardized remimazolam anesthesia

inferred← citeshttps://doi.org/10.1186/s12876-025-04306-yopenalex-snapshot

Retrospective study: analysis of risk factors and construction of prediction model for pancreatic steatosis

inferred← citeshttps://doi.org/10.1186/s12911-025-03033-4openalex-snapshot

Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit

inferred← citeshttps://doi.org/10.1186/s12938-025-01462-wopenalex-snapshot

CT radiomics-based explainable machine learning model for accurate differentiation of malignant and benign endometrial tumors: a two-center study

inferred← citeshttps://doi.org/10.1186/s13020-025-01250-7openalex-snapshot

Reinforcement learning for LLM-based explainable TCM prescription recommendation with implicit preferences from small language models

inferred← citeshttps://doi.org/10.31083/fbl44127openalex-snapshot

Biophysical Properties of the Extracellular Matrix in Cancer: Insights Into Immunotherapy

inferred← citeshttps://doi.org/10.3389/fdgth.2026.1767120openalex-snapshot

Algebraic evaluation of optimization in tumors classification with numerical assessments via a flask–react web interface

inferred← citeshttps://doi.org/10.3389/fmicb.2026.1863564openalex-snapshot

The female reproductive tract microbiotas, inflammation, and gynecological conditions: mechanisms, therapeutic advances, and future perspectives

inferred← citeshttps://doi.org/10.3389/fonc.2026.1782613openalex-snapshot

Multicenter machine learning study for long-term prediction of acute kidney injury after complete mesocolic excision: integrating inflammatory biomarkers and transfusion-related risk factors

inferred← citeshttps://doi.org/10.3389/fvets.2025.1680448openalex-snapshot

Interplay between nutrition, microbiota, and immunity in rotavirus infection: insights from human and animal models

inferred← citeshttps://doi.org/10.3389/or.2026.1744721openalex-snapshot

A new paradigm for retroperitoneal leiomyosarcoma: integrating transcriptomic subtyping and surgical risk stratification for AI-guided drug repurposing

inferred← citeshttps://doi.org/10.3390/a18120772openalex-snapshot

Recent Trends in Machine Learning for Healthcare Big Data Applications: Review of Velocity and Volume Challenges

inferred← citeshttps://doi.org/10.3390/bioengineering12070721openalex-snapshot

Machine Learning Models Derived from [18F]FDG PET/CT for the Prediction of Recurrence in Patients with Thymomas

inferred← citeshttps://doi.org/10.3390/buildings16010185openalex-snapshot

Benchmarking Automated Machine Learning for Building Energy Performance Prediction: A Comparative Study with SHAP-Based Interpretability

inferred← citeshttps://doi.org/10.3390/diagnostics15030273openalex-snapshot

Automated Machine Learning in Dentistry: A Narrative Review of Applications, Challenges, and Future Directions

inferred← citeshttps://doi.org/10.3390/electronics15051044openalex-snapshot

NanoCNN: Minority-Aware Neural Architecture Search for Edge Arrhythmia Classification

inferred← citeshttps://doi.org/10.3390/fi18080383openalex-snapshot

AutoML for Network-Based Intrusion Detection: Evaluation Practice, Dataset Quality, and Deployment Constraints

inferred← citeshttps://doi.org/10.3390/metabo15110725openalex-snapshot

Taurasi DOCG Wines from the Campania Region: A Pilot Study with an AI Approach on a Local Grape Cultivar

inferred← citeshttps://doi.org/10.3390/sym17060823openalex-snapshot

Balanced Knowledge Transfer in MTTL-ClinicalBERT: A Symmetrical Multi-Task Learning Framework for Clinical Text Classification

inferred← citeshttps://doi.org/10.34133/research.1405openalex-snapshot

Microfluidic Chip Platforms for Red Blood Cell Storage Lesion Quality Control and Precision Transfusion

inferred← citeshttps://doi.org/10.3934/era.2026172openalex-snapshot

Trustworthy and interpretable stacking via TabNet-driven feature generation for breast cancer diagnosis

inferred← citeshttps://doi.org/10.4018/979-8-3373-5137-7.ch003openalex-snapshot

Hybrid Machine Learning Optimization Models for Disease Prediction

inferred← citeshttps://doi.org/10.64898/2026.03.13.26347938openalex-snapshot

AutoML-Multiverse: An Instability-Aware Framework for Quantifying Analytic Variability in Alzheimer’s Disease Machine-Learning Studies

inferred← citeshttps://doi.org/10.7717/peerj-cs.3193openalex-snapshot

A literature review on disease detection with automated machine learning

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.