mlsanityData to 7 Oct 2026

Medical Imaging and Machine Learning

arXiv 2103.01938 ↗First posted 2 Mar 2021eess.IV cs.CV cs.LGcited by 12

Not on the map. Why?

Abstract (arXiv)

Advances in computing power, deep learning architectures, and expert labelled datasets have spurred the development of medical imaging artificial intelligence systems that rival clinical experts in a variety of scenarios. The National Institutes of Health in 2018 identified key focus areas for the future of artificial intelligence in medical imaging, creating a foundational roadmap for research in image acquisition, algorithms, data standardization, and translatable clinical decision support systems. Among the key issues raised in the report: data availability, need for novel computing architectures and explainable AI algorithms, are still relevant despite the tremendous progress made over the past few years alone. Furthermore, translational goals of data sharing, validation of performance for regulatory approval, generalizability and mitigation of unintended bias must be accounted for early in the development process. In this perspective paper we explore challenges unique to high dimensional clinical imaging data, in addition to highlighting some of the technical and ethical considerations in developing high-dimensional, multi-modality, machine learning systems for clinical decision support.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 28 of its 71 references that are in the map. First posted on arXiv 2 Mar 2021.

Builds on

28 of 71 references.

References · 28

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16 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 2; 2024: 2; 2025: 0; 2026: 1.

12 papers.

  1. 2022Evaluation of post-hoc interpretability methods in time-series classificationcited by 53
  2. 2021Algorithm Fairness in AI for Medicine and Healthcarecited by 21
  3. 2022Labeling instructions matter in biomedical image analysiscited by 20
  4. 2021Video-rate multispectral imaging in laparoscopic surgery: First-in-human applicationcited by 6
  5. 2023Human Body Digital Twin: A Master Plancited by 5
  6. 2022On Real-time Image Reconstruction with Neural Networks for MRI-guided Radiotherapycited by 3
  7. 2024MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shotscited by 2
  8. 2022Clustering and classification of low-dimensional data in explicit feature map domain: intraoperative pixel-wise diagnosis of adenocarcinoma of a colon in a livercited by 1
  9. 2023Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economycited by 1
  10. 2022Adversarial confound regression and uncertainty measurements to classify heterogeneous clinical MRI in Mass General Brighamcited by 0
  11. 2024Lightweight, error-tolerant edge detection using memristor-enabled stochastic logicscited by 0
  12. 2026Clinical Harness for Governable Medical AI Skill Ecosystemscited by 0