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FG-AI4H deliverables overview

​Overview

The FG-AI4H Deliverables are organized under one of four pillars: (1) ethics, (2) regulations, (3) technology and (4) clinical evaluation and use cases. The following figure (taken from DEL0) illustrates the relationship of the various planned FG-AI4H deliverables.

​DEL00sc.png
(CC BY 4.0)

Availability

The following document provides a general overview of the FG-AI4H Deliverables:
  • DEL 0: Overview of the FG-AI4H deliverables (Pre-published)
The completed FG-AI4H deliverables (prepublished or published) are listed below. ​

NOTE - Published and pre-published deliverables can be​ downloaded freely.
Ethics
  • DEL 1: Ethics and governance of artificial intelligence for health (Published)
Regulatory
  • DEL 2: Overview of Regulatory Concepts on Artificial Intelligence for Health (Published)
  • DEL 2.1: Mapping of IMDRF essential principles to AI for health software (Pre-published)
  • DEL 2.2: Good practices for health applications of machine learning: Considerations for manufacturers and regulators (Published)
Technical
  • DEL 0.1: Common unified terms in artificial intelligence for health (Published)
  • DEL 3: AI4H requirement specifications Pre-published)
  • DEL 4: AI software life cycle specification (Pre-published)
  • DEL 5.1: Data requirements (Pre-published)
  • DEL 5.3: Data annotation specification (Pre-published)
  • DEL 5.4: Training and test data specification (Pre-published)
  • DEL 5.5: Data handling (Pre-published)
  • DEL 6: AI training best practices specification (Pre-published)
  • DEL 7: AI for health evaluation considerations (Pre-published)
  • DEL 7.2: AI technical test specification (Pre-published)
Clinical evaluation and use cases
  • DEL 7.4: Clinical evaluation of AI for health (Published)
  • DEL 10: AI4H use cases: Topic Description Documents (Pre-published)
  • DEL 10.2: FG-AI4H Topic Description Document for the Topic group on Dermatology (TG-Derma) (Pre-published)
  • DEL 10.4: FG-AI4H Topic Description Document for the Topic group on Falls among the elderly (TG-Falls) (Pre-published)
  • DEL 10.6: FG-AI4H Topic Description Document for the Topic group on Malaria detection (TG-Malaria) (Pre-published)
  • DEL 10.7: FG-AI4H Topic Description Document for the Topic group on Maternal and child health (TG-MCH) (Pre-published)
  • DEL 10.8: FG-AI4H Topic Description Document for the Topic group on Neurological disorders (TG-Neuro) (Pre-published)
  • DEL 10.9: FG-AI4H Topic Description Document for the Topic group on Ophthalmology (TG-Ophthalmo) (Pre-published)
  • DEL 10.10: FG-AI4H Topic Description Document for the Topic group on Outbreak detection (TG-Outbreaks) (Pre-published)
  • DEL 10.12: FG-AI4H Topic Description Document for the Topic group on AI for radiology (TG-Radiology) (Pre-published)
  • DEL 10.14: FG-AI4H Topic Description Document for the Topic group on Symptom assessment (TG-Symptom) (Pre-published)
  • DEL 10.15: FG-AI4H Topic Description Document for the Topic group on Tuberculosis (TG-TB) (Pre-published)
  • DEL 10.17: FG-AI4H Topic Description Document for the Topic group on dental diagnostics and digital dentistry (TG-Dental) (Pre-published)
  • DEL 10.20: FG-AI4H Topic Description Document for the Topic group on AI for endoscopy (TG-Endoscopy) (Pre-published)
  • DEL 10.21: FG-AI4H Topic Description Document for the Topic group on AI for musculoskeletal medicine (TG-MSK) (Pre-published)
  • DEL 10.23: FG-AI4H Topic Description Document for the Topic group on AI for traditional medicine (TG-TM) (Pre-published)
  • DEL 10.24: FG-AI4H Topic Description Document for the Topic group on AI for point-of care diagnostics (TG-POC) (Pre-published)
  • TG-Dental Output 1: Artificial intelligence in dental research: A checklist for authors and reviewers (Pre-published)
  • TG-Dental Output 2: Artificial intelligence for oral and dental healthcare: Core education curriculum (Pre-published)
  • TG-Dental Output 3: Ethical considerations on artificial intelligence in dentistry: A framework and checklist (Pre-published)
  • AHG-DT4HE Output 1: Guidance on digital technologies for COVID health emergency (Pre-published)

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