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The
Deliverables (outputs) of the Focus Group AI for Health are structured in the AI for Health Framework, which roughly corresponds to the dashed-line area in the above ecosystem diagram. Depending on their primary domain being health or ICT, the individual components of the AI for Health Framework
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This organization convenes an international network of experts and stakeholders from fields like research, practice, regulation, ethics, public health, etc, that develops guideline documentation and code. The documents address ethics, assessment/evaluation, handling, and regulation of AI for health
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solutions, covering specific use cases including AI in ophthalmology, histopathology, dentistry, malaria detection, radiology, symptom checker applications, etc. FG-AI4H has established an ad hoc group concerned with digital technologies for health emergencies, including
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Wiegand, Thomas; Lee, Naomi; Pujari, Sameer; Singh, Manjula; Xu, Shan; Lecoultre, Marc; Riviere-Cinnamond, Ana; Weicken, Eva; Wenzel, Markus; Campos, Simão; Quast, Bastiaan (2020).
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Wiegand, Thomas; Krishnamurthy, Ramesh; Kuglitsch, Monique; Lee, Naomi; Pujari, Sameer; Salathé, Marcel; Wenzel, Markus; Xu, Shan (2019-07-06).
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were ratified by the corresponding United
Nations Specialized Agency, as WHO Guidelines and ITU Recommendations respectively.
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367:"WHO and ITU establish benchmarking process for artificial intelligence in health"
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422:"Whitepaper for the ITU/WHO Focus Group on Artificial Intelligence for Health"
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The outline of the benchmarking framework was published in a commentary in
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ITU-WHO Focus Group on
Artificial Intelligence for Health
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ITU-WHO Focus Group on
Artificial Intelligence for Health
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ITU-WHO Focus Group on
Artificial Intelligence for Health
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Global Summit. Administratively, FG-AI4H was created by
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Benchmarking framework for AI in health diagnostic aids
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Use cases of the ITU-WHO Focus Group on AI for Health
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205:) is an inter-agency collaboration between the
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275:Standards drawn up by FG-AI4H are titled as:
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575:Scientific organizations established in 2018
323:ITU Telecommunication Standardization Sector
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232:came out of the Health Track of the 2018
541:Proceedings of Machine Learning Research
294:AI training best practices specification
534:"ML4H Auditing: From Paper to Practice"
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580:Regulation of artificial intelligence
570:International Telecommunication Union
429:International Telecommunication Union
328:Artificial intelligence in healthcare
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288:AI software life cycle specification
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475:"Meeting results (2018-07-09~20)"
532:Oala, Luis; Fehr, Jana (2020).
514:from the original on 2020-07-26
485:from the original on 2020-07-26
456:from the original on 2020-07-26
303:AI4H applications and platforms
285:AI4H requirements specification
225:. All documentation is public.
155:Working Groups and Topic Groups
297:AI4H evaluation considerations
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383:10.1016/S0140-6736(19)30762-7
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300:AI4H scale-up and adoption
279:AI4H ethics considerations
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317:World Health Organization
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256:2020 health workshop.
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291:Data specification
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160:Affiliations
151:Subsidiaries
128:Simao Campos
34:Abbreviation
508:www.itu.int
479:www.itu.int
450:www.itu.int
250:Chaesub Lee
234:AI for Good
230:Focus Group
123:Secretariat
79:Switzerland
559:Categories
547:: 281–317.
518:2020-07-26
489:2020-07-26
460:2021-01-22
371:The Lancet
349:References
261:The Lancet
391:0140-6736
93:Worldwide
42:Formation
512:Archived
483:Archived
454:Archived
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399:30935732
311:See also
240:. Under
223:COVID-19
209:and the
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68:Location
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187:/fgai4h
174:Website
60:Purpose
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537:(PDF)
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403:S2CID
319:(WHO)
242:ITU-T
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395:PMID
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197:The
183:.int
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