Clinical Reasoning of a Generative Artificial Intelligence Model Compared With Physicians

Cabral, Stephanie; Restrepo, Daniel; Kanjee, Zahir; Wilson, Philip; Crowe, Byron; Abdulnour, Raja-Elie; Rodman, Adam

doi:10.1001/jamainternmed.2024.0295

Cited by 29 publications

(1 citation statement)

References 5 publications

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“…Indeed, LLMs have emergent abilities in domains that were once thought to be exclusive to the human mind-passing licensing exams, solving complex cases, making probabilistic decisions, and outperforming humans in measures of clinical reasoning. [3][4][5][6] Ultimately, both the human and the LLM reached the correct diagnosis, albeit with varying degrees of diagnostic efficiency.…”

Section: Discussionmentioning

confidence: 99%

Conversations on reasoning: Large language models in diagnosis

Restrepo,

Rodman,

Abdulnour

2024

Journal of Hospital Medicine

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Section: Discussionmentioning

confidence: 99%

Conversations on reasoning: Large language models in diagnosis

Restrepo,

Rodman,

Abdulnour

2024

Journal of Hospital Medicine

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The role of artificial intelligence in life-sustaining treatment decisions: current state and future considerations

Wernly,

Guidet,

Beil

2024

Intensive Care Med

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Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine

Crowe,

Shah,

Teng

et al. 2024

J GEN INTERN MED

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Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship. Additionally, we highlight our most important generative AI ethics and equity considerations for these stakeholders. For clinicians, we recommend approaching generative AI similarly to other important biomedical advancements, critically appraising its evidence and utility and incorporating it thoughtfully into practice. For technologists developing generative AI for healthcare applications, we recommend a major frameshift in thinking away from the expectation that clinicians will “supervise” generative AI. Rather, these organizations and individuals should hold themselves and their technologies to the same set of high standards expected of the clinical workforce and strive to design high-performing, well-studied tools that improve care and foster the therapeutic relationship, not simply those that improve efficiency or market share. We further recommend deep and ongoing partnerships with clinicians and patients as necessary collaborators in this work. And for healthcare organizations, we recommend pursuing a combination of both incremental and transformative change with generative AI, directing resources toward both endeavors, and avoiding the urge to rapidly displace the human clinical workforce with generative AI. We affirm that the practice of medicine remains a fundamentally human endeavor which should be enhanced by technology, not displaced by it.

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Clinical Reasoning of a Generative Artificial Intelligence Model Compared With Physicians

Abstract: This cross-sectional study assesses the ability of a large language model to process medical data and display clinical reasoning compared with the ability of attending physicians and residents.

Cited by 29 publications

References 5 publications

Conversations on reasoning: Large language models in diagnosis

Conversations on reasoning: Large language models in diagnosis

The role of artificial intelligence in life-sustaining treatment decisions: current state and future considerations

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine

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