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Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter.
van de Sande, Davy; Van Genderen, Michel E; Smit, Jim M; Huiskens, Joost; Visser, Jacob J; Veen, Robert E R; van Unen, Edwin; Ba, Oliver Hilgers; Gommers, Diederik; Bommel, Jasper van.
Afiliación
  • van de Sande D; Department of Adult Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Van Genderen ME; Department of Adult Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands m.vangenderen@erasmusmc.nl.
  • Smit JM; Department of Adult Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Huiskens J; Pattern Recognition and Bioinformatics group, EEMCS, Delft University of Technology, Delft, The Netherlands.
  • Visser JJ; SAS Institute Inc, Health, Huizen, The Netherlands.
  • Veen RER; Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
  • van Unen E; Department of Information Technology, Chief Medical Information Officer, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Ba OH; Department of Information Technology, theme Research Suite, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Gommers D; SAS Institute Inc, Health, Huizen, The Netherlands.
  • Bommel JV; Active Medical Devices/Medical Device Software, CE Plus GmbH, Badenweiler, Germany.
BMJ Health Care Inform ; 29(1)2022 Feb.
Article en En | MEDLINE | ID: mdl-35185012
OBJECTIVE: Although the role of artificial intelligence (AI) in medicine is increasingly studied, most patients do not benefit because the majority of AI models remain in the testing and prototyping environment. The development and implementation trajectory of clinical AI models are complex and a structured overview is missing. We therefore propose a step-by-step overview to enhance clinicians' understanding and to promote quality of medical AI research. METHODS: We summarised key elements (such as current guidelines, challenges, regulatory documents and good practices) that are needed to develop and safely implement AI in medicine. CONCLUSION: This overview complements other frameworks in a way that it is accessible to stakeholders without prior AI knowledge and as such provides a step-by-step approach incorporating all the key elements and current guidelines that are essential for implementation, and can thereby help to move AI from bytes to bedside.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Investigación Biomédica Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: BMJ Health Care Inform Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Investigación Biomédica Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: BMJ Health Care Inform Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Reino Unido