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1
Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study.
Holdener, Marianne;Gut, Alain;Angerer, Alfred;
2020 JMIR mHealth and uHealth DOI: 10.2196/13244 302 views
2
Digital Medical Interview Assistant for Radiology: Opportunities and Challenges.
Denecke, Kerstin;Lombardi, Paolo;Nairz, Knud;
2022 Studies in health technology and informatics DOI: 10.3233/SHTI220345 84 views
3
ChatGPT-4 Performs Clinical Information Retrieval Tasks Utilizing Consistently More Trustworthy Resources Than Does Google Search for Queries Concerning the Latarjet Procedure.
Oeding, Jacob F;Lu, Amy Z;Mazzucco, Michael;Fu, Michael C;Taylor, Samuel A;Dines, David M;Warren, Ru...
2024 Arthroscopy : the journal of arthroscopic & relate... DOI: S0749-8063(24)00407-... 33 views
4
The performance of large language model powered chatbots compared to oncology physicians on colorectal cancer queries.
Zhou, Shan;Luo, Xiao;Chen, Chan;Jiang, Hong;Yang, Chun;Ran, Guanghui;Yu, Juan;Yin, Chengliang;
2024 International journal of surgery (London, England) DOI: 10.1097/JS9.00000000... 38 views
5
Global Health care Professionals' Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study.
Ozkan, Ecem; Tekin, Aysun; Ozkan, Mahmut Can; Cabrera, Daniel; Niven, Alexander; Dong, Yue
2025 JMIR medical education DOI: 10.2196/58801 32 views

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Mhealth mobile health measurement mobile apps user engagement user engagement scale radiology conversational user interface intelligent system medical history interview anamnesis dialog-based system artificial intelligence ai latarjet shoulder instability generative llm large language model efficiency