Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.
JMIR Med Educ
; 10: e52674, 2024 Apr 08.
Article
in En
| MEDLINE
| ID: mdl-38602313
ABSTRACT
Background:
Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis.Objective:
This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided.Methods:
Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses.Results:
ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included.Conclusions:
Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.Key words
AI; AI diagnosis; AI in medicine; ChatGPT; United States; accuracy; adolescent; adolescents; artificial intelligence; child; children; diagnostic accuracy; digital health; elder; elderly; female; investigative; laboratory investigation; laboratory investigations; mHealth; male; medical diagnosis; medical history; mobile health; older adult; older adults; older people; older person; patient history; physical examination; physical examinations; public health; teen; teenager; teenagers; teens; treatment; youth
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
Medicine
Limits:
Humans
Language:
En
Journal:
JMIR Med Educ
/
JMIR medical education
Year:
2024
Document type:
Article
Affiliation country:
Country of publication: