Management of Burns: Multi-Center Assessment Comparing AI Models and Experienced Plastic Surgeons DOI Open Access
Gianluca Marcaccini, Ishith Seth, Bryan Lim

et al.

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(9), P. 3078 - 3078

Published: April 29, 2025

Background: Burn injuries require accurate assessment for effective management, and artificial intelligence (AI) is gaining attention in burn care diagnosis, treatment planning, decision support. This study compares the effectiveness of AI-driven models with experienced plastic surgeons management. Methods: Ten anonymized images varying severity anatomical location were selected from publicly available databases. Three AI systems (ChatGPT-4o, Claude, Kimi AI) analyzed these images, generating clinical descriptions management plans. reviewed same to establish a reference standard evaluated AI-generated recommendations using five-point Likert scale accuracy, relevance, appropriateness. Statistical analyses, including Cohen’s kappa coefficient, assessed inter-rater reliability comparative accuracy. Results: showed high diagnostic agreement clinicians, ChatGPT-4o achieving highest ratings. However, varied specificity, occasionally lacking individualized considerations. Readability scores indicated that outputs more comprehensible than traditional medical literature, though some overly simplistic. coefficient suggested moderate among human evaluators. Conclusions: While demonstrate strong accuracy readability, further refinements are needed improve specificity personalization. highlights AI’s potential as supplementary tool while emphasizing need oversight ensure safe patient care.

Language: Английский

Identification and characterization of lncRNA-miRNA-mRNA tripartite network of sulfur mustard exposed patients DOI
Masoud Arabfard,

Shahram Parvin,

Mostafa Ghanei

et al.

International Immunopharmacology, Journal Year: 2025, Volume and Issue: 149, P. 114204 - 114204

Published: Feb. 6, 2025

Language: Английский

Citations

1
Comprehensive transcriptomics analysis of peripheral blood mononuclear cells in exposure to mustard gas DOI

Shahram Parvin,

Hasan Bagheri, Raheleh Halabian

et al.

International Immunopharmacology, Journal Year: 2025, Volume and Issue: 150, P. 114197 - 114197

Published: Feb. 12, 2025

Language: Английский

Citations

0
Management of Burns: Multi-Center Assessment Comparing AI Models and Experienced Plastic Surgeons DOI Open Access
Gianluca Marcaccini, Ishith Seth, Bryan Lim

et al.

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(9), P. 3078 - 3078

Published: April 29, 2025

Background: Burn injuries require accurate assessment for effective management, and artificial intelligence (AI) is gaining attention in burn care diagnosis, treatment planning, decision support. This study compares the effectiveness of AI-driven models with experienced plastic surgeons management. Methods: Ten anonymized images varying severity anatomical location were selected from publicly available databases. Three AI systems (ChatGPT-4o, Claude, Kimi AI) analyzed these images, generating clinical descriptions management plans. reviewed same to establish a reference standard evaluated AI-generated recommendations using five-point Likert scale accuracy, relevance, appropriateness. Statistical analyses, including Cohen’s kappa coefficient, assessed inter-rater reliability comparative accuracy. Results: showed high diagnostic agreement clinicians, ChatGPT-4o achieving highest ratings. However, varied specificity, occasionally lacking individualized considerations. Readability scores indicated that outputs more comprehensible than traditional medical literature, though some overly simplistic. coefficient suggested moderate among human evaluators. Conclusions: While demonstrate strong accuracy readability, further refinements are needed improve specificity personalization. highlights AI’s potential as supplementary tool while emphasizing need oversight ensure safe patient care.

Language: Английский

Citations

0