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Muse Alpha: AI-based Preliminary Diagnosis for Cognitive Thought Patterns

Authors
 Park, Hyeseong  ;  Jung, Myung Won Raymond  ;  Kim, Minji  ;  Kim, Jihye 
Citation
 Applied Human Factors and Ergonomics International, Vol.130 : 72-77, 2024-01 
Journal Title
 Applied Human Factors and Ergonomics International 
Issue Date
2024-01
Keywords
Artificial intelligence ; Health care ; Machine learning ; Medical device ; Medical system
Abstract
Recent issues of medication misuse and abuse have prompted research into utilizing big data and artificial intelligence to aid psychiatrists in determining medication dosages. Muse Alpha contributes through high-quality data collection, AI-based patient similarity analysis, and a patient-centric conversation approach. This includes the extraction of patterns of negative thoughts, achieving up to 87.5% accuracy in guiding conversations. The goal is to overcome the limitations of brief one to one interactions between doctors and patients, ensuring more accurate medication prescriptions. Discovering patterns of negative thoughts and conveying them visually to the doctor assists in providing an accurate diagnosis of the patient’s condition and aids in the precise diagnosis of medication for the patient. © 2024. Published by AHFE.
Files in This Item:
92728.pdf Download
DOI
10.54941/ahfe1004839
Appears in Collections:
7. Others (기타) > Dept. of Health Promotion (건강의학과) > 1. Journal Papers
Yonsei Authors
Kim, Ji-Hye(김지혜) ORCID logo https://orcid.org/0000-0002-5719-8180
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/212295
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