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©The Author(s) 2024.
World J Methodol. Dec 20, 2024; 14(4): 92802
Published online Dec 20, 2024. doi: 10.5662/wjm.v14.i4.92802
Published online Dec 20, 2024. doi: 10.5662/wjm.v14.i4.92802
Table 4 Detailed accuracy values for each organ system across the three Large Language Model
Organ system | ChatGPT 4 | ChatGPT 3.5 | Bard |
Cardio vascular system, respiratory system | 1.0000 | 0.6667 | 0.6667 |
Hematology | 1.0000 | 1.0000 | -1.0000 |
Respiratory | 1.0000 | 0.3333 | 0.3333 |
Respiratory system | 1.0000 | 1.0000 | 0.5000 |
Infectious diseases | 0.8039 | 0.7451 | 0.2059 |
Immune system | 0.6752 | 0.4188 | 0.2650 |
Central nervous system | 0.6585 | 0.6220 | 0.5610 |
Hematological malignancies | 0.6429 | 0.5714 | 0.4286 |
Cardio vascular system | 0.6000 | 0.6667 | 0.3333 |
Endocrine system | 0.5556 | 0.4444 | 0.5714 |
Renal | 0.5556 | 0.3704 | 0.5185 |
Gastrointestinal tract | 0.5385 | 0.2308 | 0.2308 |
- Citation: Ramasubramanian S, Balaji S, Kannan T, Jeyaraman N, Sharma S, Migliorini F, Balasubramaniam S, Jeyaraman M. Comparative evaluation of artificial intelligence systems' accuracy in providing medical drug dosages: A methodological study. World J Methodol 2024; 14(4): 92802
- URL: https://www.wjgnet.com/2222-0682/full/v14/i4/92802.htm
- DOI: https://dx.doi.org/10.5662/wjm.v14.i4.92802