Sascha K R Spencer, Patrick A Ireland, Jorja Braden, Jenny L Hepschke, Michael Lin, Helen Zhang, Jessie Channell, Hessom Razavi, Angus W Turner, Minas T Coroneo, Boaz Shulruf, Ashish Agar
A Systematic Review of Ophthalmology Education in Medical Schools: The Global Decline
Ophthalmology
rapid development artificial intelligence ai related technologies ai algorithms embedded various health information technologies assist clinicians clinical decision making study aimed explore clinicians perceive ai assistance diagnostic decision making suggest paths forward aihuman teaming clinical decision making health care study used mixed methods approach utilizing hierarchical linear modeling sentiment analysis natural language understanding techniques total 114 clinicians participated online simulation surveys 2020 2021 clinicians studied family medicine used ai algorithms aid patient diagnosis overall sentiment toward aiassisted diagnosis positive comparable diagnoses made without assistance ai however aiguided decision making congruent way clinicians typically made decisions diagnosing illnesses quantitative survey clinicians reported perceiving current ai assistance likely enhance diagnostic capability negatively influenced overall performance 0421 p02 instead clinicians diagnostic capabilities tended associated wellknown parameters education age daily habit technology use social media platforms study elucidated clinicians current perceptions sentiments toward aienabled diagnosis although sentiment positive current form ai assistance may linked efficient decision making ai algorithms well aligned subjective human reasoning clinical diagnosis developers policy makers health could gather behavioral data clinicians various disciplines help align ai algorithms unique subjective patterns reasoning humans employ clinical diagnosis