Artificial Intelligence in Clinical Decision Support

Challenges for Evaluating AI and Practical Implications Artificial intelligence (AI) promises to transform clinical decision-making processes as it has the potential to harness the vast amounts of genomic, biomarker, and phenotype data that is being generated across the health system including from health records and delivery systems, to improve the safety and quality of care

Lau AYS, Staccini P; Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications. Section Editors for the IMIA Yearbook Section on Education and Consumer Health Informatics. Yearb Med Inform. 2019 Aug;28(1):174-178. doi: 10.1055/s-0039-1677935. Epub 2019 Aug 16.

Objectives : To summarise the state of the art during the year 2018 in consumer health informatics and education, with a special emphasis on the special topic of the International Medical Informatics Association (IMIA) Yearbook for 2019: “Artificial intelligence in health: new opportunities, challenges, and practical implications”. Methods : We conducted a systematic search of