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Advanced AI models, despite performing well on medical exams, struggle significantly with patient interactions. Research indicates that these models, including OpenAI's GPT-4, fail to accurately gather medical histories and make diagnoses during dynamic conversations. The newly developed CRAFT-MD benchmark highlights these shortcomings by simulating real-life doctor-patient dialogues.
The study reveals that while GPT-4 shows impressive accuracy with structured data, its performance plummets in conversational settings. For instance, its diagnostic accuracy dropped from 82% with structured summaries to just 26% in simulated conversations. This suggests that while AI can assist in clinical work, it cannot replace the nuanced judgment of human physicians.
• AI models excel in exams but fail in patient conversations.
• GPT-4's accuracy drops significantly in dynamic diagnostic scenarios.
These AI models are designed to understand and generate human-like text, but struggle with real-time interactions.
This benchmark evaluates AI's clinical reasoning through simulated doctor-patient conversations, revealing significant performance gaps.
OpenAI develops advanced AI models like GPT-4, which are tested for their diagnostic capabilities.
Meta's Llama-2-7b model is one of the AI systems evaluated for its performance in medical diagnostics.
Mistral AI's Mistral-v2-7b model was included in the study to assess its diagnostic accuracy in conversations.
Isomorphic Labs, the AI drug discovery platform that was spun out of Google's DeepMind in 2021, has raised external capital for the first time. The $600
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