Israel Medical Association Journal

Background: The rapid evolution of large language models warrants updated benchmarking in ophthalmology to determine whether newer versions offer clinically meaningful improvements over earlier models and human comparators.

Objectives: To evaluate the diagnostic accuracy of ChatGPT-4o and ChatGPT-5 in ophthalmic cases and to compare it with previously reported results of ChatGPT-3.5, residents, and specialists.

Methods: This retrospective cohort study was conducted in one academic tertiary medical center. We reviewed data of patients admitted to the ophthalmology department from June 2022 to January 2023. We then created two clinical cases for each patient. The first was according to medical history alone (Hx). The second added the clinical examination (Hx and Ex). For each case, we asked for the three most likely diagnoses from ChatGPT-4o and ChatGPT-5. We then compared the accuracy rates (at least one correct diagnosis) with previous results of ChatGPT-3.5, residents, and specialists.

Results: A total of 63 cases were analyzed, first using history alone and then with examination findings. Based on history alone, GPT-5 and GPT-4o correctly identified 73% and 70% of cases, respectively, outperforming GPT-3.5 (54%, P < 0.05) and approaching the accuracy of residents (75%) and attending physicians (71%, P < 0.05). When physical examination was included, diagnostic accuracy rose to 94% for GPT-5 and 89% for GPT-4o, surpassing GPT-3.5 (68%, P < 0.05) and closely matching or exceeding human performance (residents 94%, attendings 87%).

Conclusions: ChatGPT-4o and ChatGPT-5 significantly outperformed GPT-3.5 and achieved diagnostic accuracy similar or even higher to clinicians in diagnosing ophthalmology cases.

Background: The primary diagnosis of functional dyspepsia (FD) is made on the basis of typical symptoms and by excluding organic gastrointestinal diseases that cause dyspeptic symptoms. However, there is difficulty reaching a diagnosis in FD.

Objectives: To assess the efficiency of the Usefulness Index (UI) test and history-taking in diagnosing FD.

Methods: A study on acute abdominal pain conducted by the World Organizati­on of Gast­roentero­logy Research Committee (OMGE) included 1333 patients presenting with acute abdo­minal pain. The clinical history-taking variables (n=23) for each pa­tient were recorded in detail using a prede­fined structured data collection sheet, and the collected data were compared with the final diagnoses.

Results: The most signifi­cant clinical history-taking variables of FD in univa­riate analysis were risk ratio (RR): location of pain at diagnosis (RR = 5.7), location of initial pain (RR = 6.5), previous similar pain (RR = 4.0), duration of pain (RR = 2.9), previous abdominal surgery (RR = 4.1), previous abdominal diseases (RR = 4.0), and previous indigestion (RR = 3.1). T­he sensi­tivity of the physicians’ initial de­cisi­on in detecting FD was 0.44, speci­fi­city 0.99 and effi­ciency 0.98; UI was 0.19 and RR 195.3. In the stepwise multivariate logistic regression analysis, the independent predictors of FD were the physicians’ initial decision (RR = 266.4), location of initial pain (RR = 3.4), duration of pain (RR = 3.1), previous abdominal surgery (RR = 3.7), previous indigestion (RR = 2.2) and vomiting (RR = 2.0).

Conclusions: The patients with upper abdominal pain initially and a previous history of abdominal surgery and indigestion tended to be at risk for FD. In these patients the UI test could help the clinician differentiate FD from other diagnoses of acute abdominal pain.