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Christopher R. Brigham
,
Waqas A. Buttar
,
Mark Bucksbaum
, and
James B. Talmage

approaches are useful tools in reducing physician burnout. 5 Other approaches, such as clinical decision-making, reflect higher risk. From clinical decision support to drug discovery, AI techniques such as machine learning (ML) and natural language processing (NLP) demonstrate immense potential to improve the quality of care and health outcomes. 6 Many of the participants in the medicolegal field are involved with workers' compensation systems. It appears that these systems are slower to adopt technology than other arenas. Therefore, it is useful to consider how AI could

in AMA Guides® Newsletter
Christopher R. Brigham
,
Waqas A. Buttar
,
Mark Bucksbaum
, and
James B. Talmage

be managed carefully to ensure its benefits outweigh the risks. I'm encouraged to see this early exploration of the opportunities and responsibilities of AI in medicine. The odyssey of AI dates back to the mid-1950s, and its advancement is intricately intertwined with the progress in computer science. The pioneering work of mathematicians, computer scientists, and psychologists led to breakthroughs in knowledge representation, search algorithms, and machine learning. 3 By the 1980s, expert systems that could mimic reasoning in specialized domains emerged. 4

in AMA Guides® Newsletter
Stephen L. Demeter

. 8. Michelen M , Manoharan L , Elkheir N , et al. Characterising long COVID: a living systematic review . BMJ Global Health. 2021 ; 6 : e005427 . doi: 10.1136/bmjgh-2021-005427 . 9. Montani D , Savale L , Noel N , et al. Post-acute COVID-19 syndrome . Eur Respir Rev. 2022 ; 31 : 210185 . doi: 10.1183/16000617.0185-2021 . 10. Pfaff ER , Girvin AT , Bennett TB , et al. Identifying who has long COVID in the USA: a machine learning approach using N3C data . Lancet Digit Health. 2022 ; 4 : e532 – e541 . 11. Ruggiero V

in AMA Guides® Newsletter