Can Humanlike Reasoning Be Replicated in Large Language Models for Clinical Decision-Making?

Shalini Kathuria Narang

doi:10.2196/103526

June 15, 2026Journal of Medical Internet ResearchOpen Access

Can Humanlike Reasoning Be Replicated in Large Language Models for Clinical Decision-Making?

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Key Points

The research aims to explore whether large language models can mimic humanlike reasoning in clinical decision-making.
Comparison of clinical reasoning tasks performed by physicians and large language models.
Qualitative analysis of the findings and implications for real-world application.
Large language models showed proficiency in certain clinical reasoning tasks but lacked nuances in decision-making.
Real-world implications suggest both potential and limitations in using AI for clinical decisions.

Implication

News article reports on large language models versus physicians in clinical reasoning tasks, indicating new implications.

Abstract

A recent study comparing physicians and large language models on clinical reasoning tasks has received widespread attention. In this News and Perspectives article, JMIR Correspondent Shalini Kathuria Narang speaks to one of the study’s researchers and reports on the real-world implications that can and cannot be drawn from its findings.

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Cite This Study

Shalini Kathuria Narang (2026) studied this question.

synapsesocial.com/papers/6a323c29d50b63ecad206731 https://doi.org/10.2196/103526

View Full Paper

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Can Humanlike Reasoning Be Replicated in Large Language Models for Clinical Decision-Making?

Key Points

Implication

Abstract

Discussion

Cite This Study

Can Humanlike Reasoning Be Replicated in Large Language Models for Clinical Decision-Making?

Key Points

Implication

Abstract

Discussion

Cite This Study

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