The Accuracy of ChatGPT in Answering FAQs, Making Clinical Recommendations, and Categorizing Patient Symptoms: A Literature Review
View abstract on PubMed
Summary
This summary is machine-generated.ChatGPT (large language model) can answer patient FAQs and categorize symptoms but has variable accuracy (20-95%). Its generalized recommendations make it unsuitable as a standalone tool for patient care.
Area Of Science
- Artificial Intelligence in Medicine
- Natural Language Processing
- Clinical Decision Support
Background
- ChatGPT, a popular large language model (LLM), shows promise in healthcare.
- Evaluating its accuracy is crucial for safe patient care applications.
- This review assesses ChatGPT's performance in answering patient FAQs, clinical recommendations, and symptom categorization.
Purpose Of The Study
- To evaluate the accuracy of ChatGPT in answering patient FAQs.
- To assess ChatGPT's ability to provide clinical recommendations.
- To determine ChatGPT's effectiveness in categorizing patient symptoms.
Main Methods
- A comprehensive literature search was performed on PubMed.
- Search terms included "ChatGPT," "accuracy," and "clinical decision-making."
- Nine studies were selected for review based on predefined criteria.
Main Results
- ChatGPT accurately answers patient FAQs and categorizes symptoms in simpler cases.
- Clinical accuracy varied significantly, ranging from 20% to 95%.
- Its variable accuracy limits its use as a standalone point-of-care tool.
Conclusions
- ChatGPT provides generalized recommendations, not individualized patient care.
- Further research is needed to identify optimal applications and integration strategies for ChatGPT in healthcare.
- Its role may be supplementary to traditional care models.
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