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A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Deep learning enables reduced gadolinium dose for contrast‐enhanced brain MRI
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ISMRM Raw data format: A proposed standard for MRI raw datasets
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Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.
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Augmented Reality Simulator for Training in Two-Dimensional Echocardiography
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Coding Neuroradiology Reports for the Northern Manhattan Stroke Study: A Comparison of Natural Language Processing and Manual Review
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General Bounds on the Number of Examples Needed for Learning Probabilistic Concepts
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Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation
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Automated Detection of Radiology Reports that Document Non-routine Communication of Critical or Significant Results
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ImageNet Large Scale Visual Recognition Challenge
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Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
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Information extraction from multi-institutional radiology reports
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Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
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Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification
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Image Sharing: Evolving Solutions in the Age of Interoperability
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A text processing pipeline to extract recommendations from radiology reports
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Design patterns for the development of electronic health record-driven phenotype extraction algorithms
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Relational machine learning for electronic health record-driven phenotyping
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Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort
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Adaptive local window for level set segmentation of CT and MRI liver lesions
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f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks
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The WU-Minn Human Connectome Project: An overview
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Least Squares Support Vector Machine Classifiers
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Image reconstruction by domain-transform manifold learning
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The FAIR Guiding Principles for scientific data management and stewardship
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Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
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Extracting Findings from Narrative Reports: Software Transferability and Sources of Physician Disagreement
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Variability in Radiologists' Interpretations of Mammograms
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A New Initiative on Precision Medicine
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Implementing Machine Learning in Health Care — Addressing Ethical Challenges
inferredcites →https://doi.org/10.1093/jamia/ocv130openalex-snapshot
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PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability
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Electronic medical record phenotyping using the anchor and learn framework
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Learning statistical models of phenotypes using noisy labeled training data
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Distributed deep learning networks among institutions for medical imaging
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The Effect of Verification on the Assessment of Imaging Techniques
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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TCIA: An information resource to enable open science
inferredcites →https://doi.org/10.1109/tmi.2014.2377694openalex-snapshot
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
inferredcites →https://doi.org/10.1109/tmi.2018.2827462openalex-snapshot
Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss
inferredcites →https://doi.org/10.1109/tmi.2018.2833635openalex-snapshot
Image Reconstruction is a New Frontier of Machine Learning
inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02080.xopenalex-snapshot
Regression Shrinkage and Selection Via the Lasso
inferredcites →https://doi.org/10.1117/1.jmi.5.3.036501openalex-snapshot
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Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium
inferredcites →https://doi.org/10.1136/amiajnl-2012-000896openalex-snapshot
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inferredcites →https://doi.org/10.1136/amiajnl-2013-001930openalex-snapshot
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Regulations and ethical considerations in digital pathology and artificial intelligence
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Artificial intelligence integration in medical imaging data
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A Review of Perceptual Expertise in Radiology-How it develops, How we can test it, and Why humans still matter in the era of Artificial Intelligence
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Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence
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Noninterpretive Uses of Artificial Intelligence in Radiology
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AUR-RRA Review: Logistics of Academic-Industry Partnerships in Artificial Intelligence
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Artificial Intelligence Literacy: Developing a Multi-institutional Infrastructure for AI Education
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Ethics of AI in Pathology
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Using DeepLabCut for markerless cardiac physiology and toxicity estimation in water fleas (Daphnia magna)
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Multistep Automated Data Labelling Procedure (MADLaP) for thyroid nodules on ultrasound: An artificial intelligence approach for automating image annotation
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Automated image label extraction from radiology reports — A review
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The potential of AI in cancer care and research
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Addressing Inaccurate Nosology in Mental Health: A Multilabel Data Cleansing Approach for Detecting Label Noise From Structural Magnetic Resonance Imaging Data in Mood and Psychosis Disorders
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Teaching cross-cultural design thinking for healthcare
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Attention deficit/hyperactivity disorder Classification based on deep spatio-temporal features of functional Magnetic Resonance Imaging
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Enhancing histopathological medical image classification for Early cancer diagnosis using deep learning and explainable AI – LIME & SHAP
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EDITORIAL: Zero-Emission Cars Are Here: How Long Until a Zero-Radiation Cath Lab?
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Understanding artificial intelligence based radiology studies: What is overfitting?
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Understanding artificial intelligence based radiology studies: CNN architecture
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Knowledge and attitudes towards artificial intelligence in imaging: a look at the quantitative survey literature
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Vision–language models as an integrative layer for clinical artificial intelligence in radiology: A systems-level perspective
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From local counterfactuals to global feature importance: efficient, robust, and model-agnostic explanations for brain connectivity networks
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Understanding calibration of deep neural networks for medical image classification
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The role of AI for improved management of breast cancer: Enhanced diagnosis and health disparity mitigation
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Artificial intelligence for breast cancer detection and its health technology assessment: A scoping review
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Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging
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AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging
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A bird’s-eye view of deep learning in bioimage analysis
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AI applications to medical images: From machine learning to deep learning
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Ethical considerations in artificial intelligence
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Detection and localization of distal radius fractures: Deep learning system versus radiologists
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Lessons on performance, efficiency, and identity in the age of AI
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Transparency: The Missing Link to Boosting AI Transformations in Chemical Engineering
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Preparing computed tomography images for machine learning in forensic and virtual anthropology
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A blockchain-based protocol for tracking user access to shared medical imaging
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Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force
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Artificial intelligence for diagnosis of fractures on plain radiographs: A scoping review of current literature
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The 2021 landscape of FDA-approved artificial intelligence/machine learning-enabled medical devices: An analysis of the characteristics and intended use
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AI-powered radiology report simplification in Arabic: A prospective evaluation of patient-perceived understandability and clinical safety
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Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from Chinese Association of Radiologists
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Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
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Musculoskeletal trauma imaging in the era of novel molecular methods and artificial intelligence
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Anatomy-aware self-supervised learning for anomaly detection in chest radiographs
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A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop
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Trustworthiness of Artificial Intelligence Models in Radiology and the Role of Explainability
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Secondary use of radiological imaging data: Vanderbilt’s ImageVU approach
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Bibliometric Analysis on Examining Triage and Digital Triage Results in Emergency Departments
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Intelligent Imaging: Radiomics and Artificial Neural Networks in Heart Failure
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Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging
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Analysis of Robotics, Artificial intelligence and Machine learning in the field of healthcare sector
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Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis
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Semi-supervised classification of radiology images with NoTeacher: A teacher that is not mean
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Handling data heterogeneity with generative replay in collaborative learning for medical imaging
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RadFormer: Transformers with global–local attention for interpretable and accurate Gallbladder Cancer detection
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Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
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Emerging ethical issues raised by highly portable MRI research in remote and resource-limited international settings
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On the justification of justification in radiation protection - legal and sociological considerations
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Future Directions in Artificial Intelligence
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Bone and Soft Tissue Tumors
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The impact of artificial intelligence and machine learning in organ retrieval and transplantation: A comprehensive review
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Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
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Automated O-RADS Risk Stratification Using a Large Language Model Analysis of Narrative Ultrasound Reports
inferred← citeshttps://doi.org/10.1016/s2589-7500(20)30025-xopenalex-snapshot
Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study
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Deep learning for pancreatic cancer detection: current challenges and future strategies
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Causality matters in medical imaging
inferred← citeshttps://doi.org/10.1038/s41597-022-01441-zopenalex-snapshot
REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays
inferred← citeshttps://doi.org/10.1038/s41598-021-82665-8openalex-snapshot
Applying artificial intelligence to longitudinal imaging analysis of vestibular schwannoma following radiosurgery
inferred← citeshttps://doi.org/10.1038/s41598-022-20996-wopenalex-snapshot
Automated fracture screening using an object detection algorithm on whole-body trauma computed tomography
inferred← citeshttps://doi.org/10.1038/s41598-023-36435-3openalex-snapshot
The impact of AI suggestions on radiologists’ decisions: a pilot study of explainability and attitudinal priming interventions in mammography examination
inferred← citeshttps://doi.org/10.1038/s41598-023-39809-9openalex-snapshot
A pilot radiometabolomics integration study for the characterization of renal oncocytic neoplasia
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The future of digital health with federated learning
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Designing clinically translatable artificial intelligence systems for high-dimensional medical imaging
inferred← citeshttps://doi.org/10.1053/j.ro.2023.01.005openalex-snapshot
Artificial Intelligence in Radiology: Overview of Application Types, Design, and Challenges
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The International Radiomics Platform – An Initiative of the German and Austrian Radiological Societies – First Application Examples
inferred← citeshttps://doi.org/10.1055/a-1306-7590openalex-snapshot
Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method
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Images Are Data: A Breast Imaging Perspective on a Contemporary Paradigm
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The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play
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Bilder sind Daten: Eine Perspektive der Brustbildgebung auf ein zeitgenössisches Paradigma
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Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions
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Artificial Intelligence in Radiology: Unlocking New Dimensions of Value
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Artificial Intelligence in Emergency Radiology: Current Applications, Challenges, and Future Directions
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Artificial Intelligence in Medical Imaging: Navigating the Artificial Intelligence Trilemma Toward Responsible Clinical Translation
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Reimagining Radiology in the Artificial Intelligence Era: The Global South Radiology AI Implementation Framework
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Medical imaging: Challenges and future directions in AI-Based systems
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Predictive analysis of fuel oil consumption in vessels: interpretable modelling with emphasis on load conditions
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Explainable AI for automated respiratory misalignment detection in PET/CT imaging
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Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?
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Artificial Intelligence plus Human Interpretation for Thyroid Nodule Risk Stratification: An Image Similarity Model Keeps the Physician in the Loop
inferred← citeshttps://doi.org/10.1093/database/baaa010openalex-snapshot
Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
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Accounting for data variability in multi-institutional distributed deep learning for medical imaging
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ACR’s Connect and AI-LAB technical framework
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Resource requirements to accelerate clinical applications of next-generation sequencing and radiomics: workshop commentary and review
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Artificial Intelligence and Deep Learning in Diagnostic Radiology—Is This The Next Phase of Scientific and Technological Development?
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Pediatric procedures in endoscopy and radiology: clinical considerations
inferred← citeshttps://doi.org/10.1097/icu.0000000000000785openalex-snapshot
Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization
inferred← citeshttps://doi.org/10.1097/mnm.0000000000001786openalex-snapshot
Review of artificial intelligence clinical applications in Nuclear Medicine
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Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors
inferred← citeshttps://doi.org/10.1097/mpa.0000000000001603openalex-snapshot
Prediagnostic Image Data, Artificial Intelligence, and Pancreatic Cancer
inferred← citeshttps://doi.org/10.1097/mpa.0000000000001762openalex-snapshot
Artificial Intelligence and Early Detection of Pancreatic Cancer
inferred← citeshttps://doi.org/10.1097/rct.0000000000001279openalex-snapshot
Radiogenomics: A Valuable Tool for the Clinical Assessment and Research of Ovarian Cancer
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Advancing Medical Imaging Research Through Standardization
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NIH Funding for Artificial Intelligence in Surgical Specialties: Allocation and Alignment with US Disease Burden
inferred← citeshttps://doi.org/10.1109/access.2020.2978406openalex-snapshot
Deep Learning for Underwater Visual Odometry Estimation
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Lightweight Mask RCNN for Warship Detection and Segmentation
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A Review of Feature Selection and HyperparameterOptimization Techniques for Breast Cancer Detection on thermograms Images
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Applications of AI in Healthcare Sector for Enhancement of Medical Decision Making and Quality of Service
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An Approach for Asbestos-related Pleural Plaque Detection
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A Comparative Study of Deep Learning Approaches to Improve the Diagnosis of Neurological Disorders
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Artificial intelligent for speech reproduction of information and knowledge of ancient books
inferred← citeshttps://doi.org/10.1109/icassp43922.2022.9746827openalex-snapshot
Privacy Sensitive Speech Analysis Using Federated Learning to Assess Depression
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Robust Localization of Key Fob Using Channel Impulse Response of Ultra Wide Band Sensors for Keyless Entry Systems
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Enhanced CNN-Based Decision Support Framework for Gastrointestinal Neuroendocrine Tumors using Inception-Resnet-V2
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