ENTERPRISE AI ANALYSIS BY OWN YOUR AI
A comparison of the performance of Chinese large language models and ChatGPT throughout the entire clinical workflow
This study evaluates the performance of Chinese large language models (Doubao, ERNIE Bot 3.5) and ChatGPT-4 in simulated patient clinical workflows, comparing them to human emergency physicians. Findings indicate Doubao performs comparably to ChatGPT-4, both outperforming human doctors in diagnostic questions and management. The rapid advancement of LLMs, especially ChatGPT-4 over ChatGPT-3.5, highlights their significant potential as decision support tools in healthcare, though limitations exist regarding active information solicitation and potential for plausible but incorrect explanations.
Key Executive Impact
Our analysis reveals the following critical metrics for business leaders.
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Average accuracy proportion in diagnosis questions for all three models.
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LLMs superior to human physicians in diagnostic questions and management.
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ChatGPT-4 average correct proportion in diagnosis, outperforming ChatGPT-3.5.
Deep Analysis & Enterprise Applications
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97%
Average accuracy in diagnosis questions for all three models (ChatGPT-4, Doubao, ERNIE Bot 3.5).
| Aspect | ChatGPT-4 | Doubao | ERNIE Bot 3.5 |
|---|---|---|---|
| Differential Diagnosis | 0.74±0.12 | 0.71±0.12 | 0.63±0.14 |
| Diagnostic Questions | 0.78±0.13 | 0.79±0.14 | 0.72±0.16 |
| Diagnosis | 0.99±0.03 | 0.98±0.09 | 0.97±0.07 |
| Management | 0.84±0.10 | 0.81±0.11 | 0.76±0.14 |
Superior
LLMs performance compared to human emergency fellow physicians in diagnostic questions and management.
| Aspect | ChatGPT-4 | Fellow Physicians |
|---|---|---|
| Differential Diagnosis | 0.74±0.12 | 0.66±0.19 |
| Diagnostic Questions | 0.78±0.13 | 0.70±0.15 |
| Diagnosis | 0.99±0.03 | 0.98±0.08 |
| Management | 0.84±0.10 | 0.72±0.18 |
LLM Evaluation Workflow
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Case Study: Chest Pain Differential Diagnosis
In Case 2, an LLM (unspecified, likely ERNIE Bot 3.5 from context) dismissed Acute Coronary Syndrome (ACS) too easily, reasoning that the chest pain was not severe enough and the patient did not have difficulty breathing. The study highlights that while LLMs provide plausible explanations, they can be incorrect, emphasizing the need for LLMs as decision support tools rather than replacements for human doctors, especially in critical scenarios like chest pain where ACS should always be considered.
Rapid
Pace of LLM advancement, exemplified by ChatGPT-4's superior performance over ChatGPT-3.5 in just two years.
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