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Explainable Artificial Intelligence for Human Decision Support System in the Medical Domain

https://doi.org/10.3390/make3030037
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1 of the 30 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1155/2021/6633755 (notice 2023-09-27).

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What this work says

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

inferredcites →https://doi.org/10.1002/mp.13264openalex-snapshot
Deep learning in medical imaging and radiation therapy
inferredcites →https://doi.org/10.1007/978-3-030-50334-5_4openalex-snapshot
Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support
inferredcites →https://doi.org/10.1007/978-3-030-51924-7_8openalex-snapshot
Explainable Agents for Less Bias in Human-Agent Decision Making
inferredcites →https://doi.org/10.1007/978-3-030-82017-6_3openalex-snapshot
Comparison of Contextual Importance and Utility with LIME and Shapley Values
inferredcites →https://doi.org/10.1007/978-3-030-82017-6_4openalex-snapshot
ciu.image: An R Package for Explaining Image Classification with Contextual Importance and Utility
inferredcites →https://doi.org/10.1007/978-3-319-57959-7openalex-snapshot
The EU General Data Protection Regulation (GDPR)
inferredcites →https://doi.org/10.1007/978-3-319-93000-8_63openalex-snapshot
A Deep Learning Approach for Red Lesions Detection in Video Capsule Endoscopies
inferredcites →https://doi.org/10.1016/j.inffus.2021.05.009openalex-snapshot
Notions of explainability and evaluation approaches for explainable artificial intelligence
inferredcites →https://doi.org/10.1073/pnas.1716999115openalex-snapshot
An explainable deep machine vision framework for plant stress phenotyping
inferredcites →https://doi.org/10.1109/access.2018.2870052openalex-snapshot
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
inferredcites →https://doi.org/10.1109/access.2020.2976199openalex-snapshot
Explainable Machine Learning for Scientific Insights and Discoveries
inferredcites →https://doi.org/10.1109/dicta47822.2019.8945986openalex-snapshot
Explaining Machine Learning-Based Classifications of In-Vivo Gastral Images
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/mcg.2018.042731661openalex-snapshot
Visual Analytics for Explainable Deep Learning
inferredcites →https://doi.org/10.1145/2939672.2939778openalex-snapshot
"Why Should I Trust You?"
inferredcites →https://doi.org/10.1145/3236009openalex-snapshot
A Survey of Methods for Explaining Black Box Models
inferredcites →https://doi.org/10.1155/2021/6633755openalex-snapshot
PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation
inferredcites →https://doi.org/10.1186/s12911-020-01332-6openalex-snapshot
Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
inferredcites →https://doi.org/10.1515/9781400881970-018openalex-snapshot
17. A Value for n-Person Games
inferredcites →https://doi.org/10.1613/jair.1.13200openalex-snapshot
Explainable Deep Learning: A Field Guide for the Uninitiated
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.491openalex-snapshot
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?
inferredcites →https://doi.org/10.23919/mipro.2018.8400040openalex-snapshot
Explainable artificial intelligence: A survey
inferredcites →https://doi.org/10.3390/e23010018openalex-snapshot
Explainable AI: A Review of Machine Learning Interpretability Methods
inferredcites →https://doi.org/10.48550/arxiv.1702.08608openalex-snapshot
Towards A Rigorous Science of Interpretable Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.1705.07874openalex-snapshot
A Unified Approach to Interpreting Model Predictions
inferredcites →https://doi.org/10.48550/arxiv.1708.08296openalex-snapshot
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models
inferredcites →https://doi.org/10.48550/arxiv.1712.06657openalex-snapshot
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology
inferredcites →https://doi.org/10.48550/arxiv.1712.09923openalex-snapshot
What do we need to build explainable AI systems for the medical domain?
inferredcites →https://doi.org/10.48550/arxiv.2009.13996openalex-snapshot
Explainable AI without Interpretable Model
inferredcites →https://doi.org/10.65109/kczb5817openalex-snapshot
Explainable Agents and Robots: Results from a Systematic Literature Review

What points at this work

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

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inferred← citeshttps://doi.org/10.1007/978-3-031-67751-9_8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-70074-3_10openalex-snapshot
py_ciu_image: A Python Library for Explaining Image Classification with Contextual Importance and Utility
inferred← citeshttps://doi.org/10.1007/978-3-031-96231-8_26openalex-snapshot
Explainable AI-Driven Feature Selection for Improved Intrusion Detection Systems in the Internet of Medical Things
inferred← citeshttps://doi.org/10.1007/978-3-031-97557-8_11openalex-snapshot
Explainable Artificial Intelligence for Doctors Decision Support in Diagnosing Spinal Pathologies
inferred← citeshttps://doi.org/10.1007/978-3-032-01536-5_38openalex-snapshot
ENHANCING IoMT Security with Explainable Machine Learning: A Case Study on the CICIOMT2024 Dataset
inferred← citeshttps://doi.org/10.1007/978-3-032-21514-7_2openalex-snapshot
A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis
inferred← citeshttps://doi.org/10.1007/978-3-032-21966-4_39openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-22114-8_40openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-25631-7_31openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-96-6960-8_28openalex-snapshot
Informed Deep Abstaining Classifier: Investigating Noise-Robust Training for Diagnostic Decision Support Systems Systems
inferred← citeshttps://doi.org/10.1007/978-981-97-7426-5_21openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-99-0405-1_7openalex-snapshot
Performance Comparison of Feature Selection Methods for Prediction in Medical Data
inferred← citeshttps://doi.org/10.1007/s00481-023-00761-xopenalex-snapshot
Levels of explicability for medical artificial intelligence: What do we normatively need and what can we technically reach?
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inferred← citeshttps://doi.org/10.2196/preprints.65435openalex-snapshot
Human-AI Collaboration Supporting GPT-4o Achieving Human-Level User Feedback in Emotional Support Conversations: Integrative Modeling and Prompt Engineering Approaches (Preprint)
inferred← citeshttps://doi.org/10.22541/au.167407909.97031004/v1openalex-snapshot
Evaluating Significant Features in Context-Aware Multimodal Emotion Recognition with XAI Methods
inferred← citeshttps://doi.org/10.2514/6.2024-0762openalex-snapshot
Explainable Machine Learning for Turbojet Engine Prognostic Health Management
inferred← citeshttps://doi.org/10.30773/pi.2024.0106openalex-snapshot
Contribution of Chronic Disease in Predicting Depression and Suicidal Ideation Among the Older Adult Population
inferred← citeshttps://doi.org/10.31219/osf.io/ms2kvopenalex-snapshot
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps
inferred← citeshttps://doi.org/10.31234/osf.io/3n95uopenalex-snapshot
Perceive, Understand & Predict - Empirical Indication for Facets in Subjective Information Processing Awareness
inferred← citeshttps://doi.org/10.31498/2225-6733.52.2025.350988openalex-snapshot
Cluster analysis and search query fore-casting for building an intelligent system for monitoring demand for medical licenses
inferred← citeshttps://doi.org/10.3233/jifs-235053openalex-snapshot
PS-Merge operator in the classification of gait biomarkers: A preliminary approach to eXplainable Artificial Intelligence
inferred← citeshttps://doi.org/10.32604/cmes.2024.051363openalex-snapshot
Explainable Artificial Intelligence (XAI) Model for Cancer Image Classification
inferred← citeshttps://doi.org/10.3390/a18060368openalex-snapshot
Synthesizing Explainability Across Multiple ML Models for Structured Data
inferred← citeshttps://doi.org/10.3390/app14167192openalex-snapshot
The Effect of Communicating AI Confidence on Human Decision Making When Performing a Binary Decision Task
inferred← citeshttps://doi.org/10.3390/axioms12050462openalex-snapshot
Automatic Classification of Coronary Stenosis Using Feature Selection and a Hybrid Evolutionary Algorithm
inferred← citeshttps://doi.org/10.3390/biomedinformatics3030048openalex-snapshot
Explainable Machine Learning (XAI) for Survival in Bone Marrow Transplantation Trials: A Technical Report
inferred← citeshttps://doi.org/10.3390/diagnostics13101692openalex-snapshot
Impact of Cross-Validation on Machine Learning Models for Early Detection of Intrauterine Fetal Demise
inferred← citeshttps://doi.org/10.3390/ecb2023-14339openalex-snapshot
Artificial Intelligence as an Emerging Tool for Cardiologists
inferred← citeshttps://doi.org/10.3390/electronics13142842openalex-snapshot
Explainable Artificial Intelligence-Based Decision Support Systems: A Recent Review
inferred← citeshttps://doi.org/10.3390/foods11142019openalex-snapshot
Unboxing Deep Learning Model of Food Delivery Service Reviews Using Explainable Artificial Intelligence (XAI) Technique
inferred← citeshttps://doi.org/10.3390/healthcare10010155openalex-snapshot
Artificial Intelligence Analysis of Gene Expression Predicted the Overall Survival of Mantle Cell Lymphoma and a Large Pan-Cancer Series
inferred← citeshttps://doi.org/10.3390/healthcare14131881openalex-snapshot
Explainable Machine Learning for Predicting Dengue Recovery Duration: Insights from Multi-Center Clinical Data
inferred← citeshttps://doi.org/10.3390/info15110725openalex-snapshot
AI for Decision Support: Balancing Accuracy, Transparency, and Trust Across Sectors
inferred← citeshttps://doi.org/10.3390/jcdd10050202openalex-snapshot
Artificial Intelligence Technologies in Cardiology
inferred← citeshttps://doi.org/10.3390/jpm11111213openalex-snapshot
Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization
inferred← citeshttps://doi.org/10.3390/jpm12030480openalex-snapshot
Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges
inferred← citeshttps://doi.org/10.3390/make5040079openalex-snapshot
Explainable Stacked Ensemble Deep Learning (SEDL) Framework to Determine Cause of Death from Verbal Autopsies
inferred← citeshttps://doi.org/10.3390/make6030071openalex-snapshot
A Cognitive Load Theory (CLT) Analysis of Machine Learning Explainability, Transparency, Interpretability, and Shared Interpretability
inferred← citeshttps://doi.org/10.3390/make7040168openalex-snapshot
XIMED: A Dual-Loop Evaluation Framework Integrating Predictive Model and Human-Centered Approaches for Explainable AI in Medical Imaging
inferred← citeshttps://doi.org/10.3390/math11143145openalex-snapshot
Predicting Depression during the COVID-19 Pandemic Using Interpretable TabNet: A Case Study in South Korea
inferred← citeshttps://doi.org/10.3390/rs14153565openalex-snapshot
Offshore Oil Slick Detection: From Photo-Interpreter to Explainable Multi-Modal Deep Learning Models Using SAR Images and Contextual Data
inferred← citeshttps://doi.org/10.3390/s22176338openalex-snapshot
Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)
inferred← citeshttps://doi.org/10.36227/techrxiv.23949135openalex-snapshot
Endorsed Attributions: eXplainable AI (XAI) with Voting Mechanism with Application in Healthcare
inferred← citeshttps://doi.org/10.36227/techrxiv.23949135.v1openalex-snapshot
Endorsed Attributions: eXplainable AI (XAI) with Voting Mechanism withApplication in Healthcare
inferred← citeshttps://doi.org/10.3892/ol.2025.15039openalex-snapshot
Future prospects of deep learning in esophageal cancer diagnosis and clinical decision support (Review)
inferred← citeshttps://doi.org/10.4018/978-1-6684-3791-9.ch011openalex-snapshot
Basic Issues and Challenges on Explainable Artificial Intelligence (XAI) in Healthcare Systems
inferred← citeshttps://doi.org/10.4018/978-1-6684-8127-1.ch001openalex-snapshot
A Comprehensive Review of Trustworthy, Ethical, and Explainable Computer Vision Advancements in Online Social Media
inferred← citeshttps://doi.org/10.4018/979-8-3693-4439-2.ch012openalex-snapshot
Explainable AI (EXAI) for Smart Healthcare Automation
inferred← citeshttps://doi.org/10.4236/jilsa.2026.182006openalex-snapshot
Explainable AI: Enhancing Clinician Trust and Accuracy in Prostate Cancer Diagnosis
inferred← citeshttps://doi.org/10.4324/9781032634487-14openalex-snapshot
Social Acceptance of Artificial Intelligence in Biobanking
inferred← citeshttps://doi.org/10.48175/ijarsct-17257openalex-snapshot
SignSense: AI Framework for Sign Language Recognition
inferred← citeshttps://doi.org/10.51983/ajsat-2023.12.2.4072openalex-snapshot
Enhancing Maternal Outcome Prediction Using Explainable Artificial Intelligence for Women of Childbearing Age
inferred← citeshttps://doi.org/10.55162/mcet.05.160openalex-snapshot
Explainable Prediction of features contributing to Intrusion Detection using ML algorithms and LIME
inferred← citeshttps://doi.org/10.5772/intechopen.1011279openalex-snapshot
Explainable AI in Health Care: Trust and Transparency in AI-Powered Medical Diagnosis
inferred← citeshttps://doi.org/10.59388/pm00357openalex-snapshot
Discussions on Neuroscience of Decision-Making
inferred← citeshttps://doi.org/10.61467/2007.1558.2024.v15i5.569openalex-snapshot
Clustering Opinion Polarity of Student’s Strategies as Clues for Motivation
inferred← citeshttps://doi.org/10.69882/adba.iteb.2025011openalex-snapshot
Transparency in Decision-Making: The Role of Explainable AI (XAI) in Customer Churn Analysis
inferred← citeshttps://doi.org/10.7287/peerj-cs.1253v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Explainability of deep learning models in medical video analysis: a survey (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1253v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Explainability of deep learning models in medical video analysis: a survey (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1253v0.1/reviews/3openalex-snapshot
Peer Review #3 of "Explainability of deep learning models in medical video analysis: a survey (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1253v0.1/reviews/4openalex-snapshot
Peer Review #4 of "Explainability of deep learning models in medical video analysis: a survey (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1253v0.2/reviews/2openalex-snapshot
Peer Review #2 of "Explainability of deep learning models in medical video analysis: a survey (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj-cs.1253openalex-snapshot
Explainability of deep learning models in medical video analysis: a survey
inferred← citeshttps://doi.org/10.7717/peerj-cs.2051openalex-snapshot
Predicting inmate suicidal behavior with an interpretable ensemble machine learning approach in smart prisons
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.