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Skip search results from other journals and go to results- 5 JMIR Medical Informatics
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Evaluation of AI-Driven LabTest Checker for Diagnostic Accuracy and Safety: Prospective Cohort Study
These tools use algorithms and databases to generate potential diagnoses based on user inputs.
A notable study conducted by Semigran et al [11] scrutinized the diagnostic precision of 23 distinct symptom checkers, comparing their outcomes against physician diagnoses. The investigation disclosed that symptom checkers achieved accurate diagnoses in 34% of instances, while physicians achieved 58% accuracy.
JMIR Med Inform 2024;12:e57162
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This feedback consists of patient outcomes, test results, and final diagnoses [27,28]. Similar to traditional CDSSs, generative AI systems can enhance this feedback loop [29]. However, a gap previously existed in the systematic comparison of differential diagnoses with final diagnoses through a feedback loop [27]. Given this background, it remains less explored how effectively these AI systems integrate their feedback into clinical workflow.
JMIR Form Res 2024;8:e59267
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Discussion with domain experts revealed that while DEVO is capable of responding to queries to find visual features associated with metaphoric terms and vice versa, linking the dermoscopic terms to differential diagnoses would significantly enhance its clinical utility. A list of differential diagnoses indicates many possible diagnoses that share similar features to the patient’s symptoms and signs.
JMIR Med Inform 2024;12:e49613
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The model’s accuracy was compared with physicians’ diagnoses to validate its effectiveness in image-based deep learning. The potential future development of the multimodal AI approach for classifying middle ear diseases is also discussed.
GPT-4 V has been available as an image recognition model since September 25, 2023. This study’s design was divided into two phases: (1) establishing a model with appropriate prompts and (2) validating the ability of the optimal prompt model to classify images (Figure 1).
JMIR AI 2024;3:e58342
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Evaluating ChatGPT-4’s Diagnostic Accuracy: Impact of Visual Data Integration
A typical case description included demographic information, chief complaints, history of present illness, results of physical examinations, and investigative findings leading to diagnoses. The final diagnoses were typically determined by the authors of the case reports.
JMIR Med Inform 2024;12:e55627
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Two physicians (KS and SF) independently assessed the diagnoses and achieved an agreement rate of 1.00. The DI of Q2 was 0.4 or higher for symptomatology or clinical reasoning and diseases and 0.3 or higher for general theory, physical examination, and clinical techniques. The overall GM-ITE scores had a high identification index of 0.47.
JMIR Med Educ 2024;10:e54401
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