大型语言模型改善了患者治疗效果吗？
一项新的综述研究表明，大型语言模型（LLMs）在改善患者临床结局方面尚未取得显著成效。尽管这些模型在医疗对话和辅助诊断中表现出色，但实际转化为更好的患者健康结果仍面临挑战。综述提醒，技术进步不等于临床获益，需更严谨的研究验证其真实影响。
相关报道
The article suggests that LLMs may rely on crystallized intelligence (learned knowledge) rather than fluid intelligence (genuine reasoning), meaning their apparent reasoning abilities could stem from memorized training data rather than true understanding.
The article argues that LLMs, unlike traditional programming abstractions, do not provide a reliable higher-level abstraction because they lack deterministic, verifiable behavior. While they can generate code or text, the results are probabilistic and require extensive verification, making them a fundamentally different tool rather than a genuine abstraction layer.