⚡ Quick Summary
This study evaluated the diagnostic accuracy of ChatGPT in comparison to clinical diagnoses for common surgical conditions, specifically acute appendicitis, acute cholecystitis, and diverticulitis. The findings revealed a significant difference in accuracy, particularly for acute cholecystitis and diverticulitis, suggesting that while ChatGPT can be a valuable support tool, it is not yet a replacement for clinical judgment.
🔍 Key Details
- 📊 Study Design: Observational cross-sectional cohort study
- 🧩 Conditions Analyzed: Acute appendicitis, acute cholecystitis, diverticulitis
- ⚙️ AI Technology: ChatGPT (version 3.5)
- 🏆 Key Findings: Significant difference in diagnostic accuracy compared to clinical diagnoses
🔑 Key Takeaways
- 🤖 ChatGPT demonstrated inferior accuracy in diagnosing acute cholecystitis and diverticulitis.
- 📉 Misdiagnosis was linked to specific symptoms affecting ChatGPT’s decision-making.
- 🔍 AI’s Role: ChatGPT can serve as a support tool in environments with limited resources.
- 📈 Statistical Analysis: Fisher’s exact test revealed significant differences in diagnostic outcomes.
- 🌍 Military Medicine: The study highlights the potential of AI in military health care settings.
- 🔬 Continued Research: Further studies are needed to evaluate AI performance in complex clinical scenarios.
📚 Background
Accurate and timely medical diagnostics are crucial, especially in military health care settings where access to advanced diagnostic tools may be limited. The integration of artificial intelligence, such as ChatGPT, into clinical decision-making processes could enhance diagnostic capabilities, particularly in remote or austere environments.
🗒️ Study
The study involved collecting data from clinical scenarios that reflected typical presentations of three common surgical conditions. Researchers analyzed various patient data inputs, including age, gender, symptoms, and laboratory values, to create scenarios for ChatGPT to diagnose. The output was then compared to expected clinical diagnoses to assess accuracy.
📈 Results
The analysis revealed a statistically significant difference between ChatGPT’s diagnostic outcomes and those made by clinical providers, particularly for acute cholecystitis and diverticulitis. The results indicated that while ChatGPT can provide valuable insights, its diagnostic accuracy is not yet on par with that of trained medical professionals.
🌍 Impact and Implications
The findings of this study underscore the potential of AI as a diagnostic support tool in military medicine and other settings where resources are constrained. However, the results also highlight the need for ongoing research to improve AI diagnostic capabilities and ensure that it complements rather than replaces human expertise in clinical decision-making.
🔮 Conclusion
This study illustrates the promise of AI in enhancing diagnostic accuracy in challenging environments. While ChatGPT shows potential as a supportive tool for clinicians, its current limitations necessitate further research and development. The future of AI in healthcare is bright, but it is essential to approach its integration with caution and a commitment to improving its accuracy.
💬 Your comments
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Comparing Diagnostic Accuracy of ChatGPT to Clinical Diagnosis in General Surgery Consults: A Quantitative Analysis of Disease Diagnosis.
Abstract
INTRODUCTION: This study addressed the challenge of providing accurate and timely medical diagnostics in military health care settings with limited access to advanced diagnostic tools, such as those encountered in austere environments, remote locations, or during large-scale combat operations. The primary objective was to evaluate the utility of ChatGPT, an artificial intelligence (AI) language model, as a support tool for health care providers in clinical decision-making and early diagnosis.
MATERIALS AND METHODS: The research used an observational cross-sectional cohort design and exploratory predictive techniques. The methodology involved collecting and analyzing data from clinical scenarios based on common general surgery diagnoses-acute appendicitis, acute cholecystitis, and diverticulitis. These scenarios incorporated age, gender, symptoms, vital signs, physical exam findings, laboratory values, medical and surgical histories, and current medication regimens as data inputs. All collected data were entered into a table for each diagnosis. These tables were then used for scenario creation, with scenarios written to reflect typical patient presentations for each diagnosis. Finally, each scenario was entered into ChatGPT (version 3.5) individually, with ChatGPT then being asked to provide the leading diagnosis for the condition based on the provided information. The output from ChatGPT was then compared to the expected diagnosis to assess the accuracy.
RESULTS: A statistically significant difference between ChatGPT’s diagnostic outcomes and clinical diagnoses for acute cholecystitis and diverticulitis was observed, with ChatGPT demonstrating inferior accuracy in controlled test scenarios. A secondary outcome analysis looked at the relationship between specific symptoms and diagnosis. The presence of these symptoms in incorrect diagnoses indicates that they may adversely impact ChatGPT’s diagnostic decision-making, resulting in a higher likelihood of misdiagnosis. These results highlight AI’s potential as a diagnostic support tool but underscore the importance of continued research to evaluate its performance in more complex and varied clinical scenarios.
CONCLUSIONS: In summary, this study evaluated the diagnostic accuracy of ChatGPT in identifying three common surgical conditions (acute appendicitis, acute cholecystitis, and diverticulitis) using comprehensive patient data, including age, gender, medical history, medications, symptoms, vital signs, physical exam findings, and basic laboratory results. The hypothesis was that ChatGPT might display slightly lower accuracy rates than clinical diagnoses made by medical providers. The statistical analysis, which included Fisher’s exact test, revealed a significant difference between ChatGPT’s diagnostic outcomes and clinical diagnoses, particularly in acute cholecystitis and diverticulitis cases. Therefore, we reject the null hypothesis, as the results indicated that ChatGPT’s diagnostic accuracy significantly differs from clinical diagnostics in the presented scenarios. However, ChatGPT’s overall high accuracy suggests that it can reliably support clinicians, especially in environments where diagnostic resources are limited, and can serve as a valuable tool in military medicine.
Author: [‘Meier H’, ‘McMahon R’, ‘Hout B’, ‘Randles J’, ‘Aden J’, ‘Rizzo JA’]
Journal: Mil Med
Citation: Meier H, et al. Comparing Diagnostic Accuracy of ChatGPT to Clinical Diagnosis in General Surgery Consults: A Quantitative Analysis of Disease Diagnosis. Comparing Diagnostic Accuracy of ChatGPT to Clinical Diagnosis in General Surgery Consults: A Quantitative Analysis of Disease Diagnosis. 2025; (unknown volume):(unknown pages). doi: 10.1093/milmed/usaf168