AI’s Threat to the Medical Profession

Fogo, Agnes B.; Kronbichler, Andreas; Bajema, Ingeborg M.

doi:10.1001/jama.2024.0018

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…The clinical practice must be always guided by the clinician's comprehension of the relationship between the input given and the output provided by the AI tools. They must be developed in such a way that they could provide the possibility to reconstruct the link between input and outputs so that it will be possible a real supervision [9].…”

Section: Editorialmentioning

confidence: 99%

Artificial Intelligence for Personalized Perioperative Medicine

Bignami,

Panizzi,

Bellini

2024

Cureus

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The development of artificial intelligence (AI) is disruptive and unstoppable, also in medicine. Because of the enormous quantity of data recorded during continuous monitoring and the peculiarity of our specialty where stratification and mitigation risk are some of the core aspects, anesthesiology and postoperative intensive care are fertile fields where new technologies find ample room for expansion.Recently, research efforts have focused on the development of a holistic technology that globally embraces the entire perioperative period rather than a fragmented approach where AI is developed to carry out specific tasks. This could potentially revolutionize the perioperative medicine we know today. In fact, AI will be able to expand clinician's ability to interpret, adapt, and ultimately act in a complex reality with facets that are too complex to be managed all at the same time and in a holistic manner.With the support of new tools, as healthcare professionals we have the moral obligation to govern this transition, allowing an ethical and sustainable development of these technologies and avoiding being overwhelmed by them. We should welcome this transhumanist tension which does not aim at the replacement of human capabilities or even at the integration of these but rather at the expansion of a "single intelligence".

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Section: Editorialmentioning

confidence: 99%

Artificial Intelligence for Personalized Perioperative Medicine

Bignami,

Panizzi,

Bellini

2024

Cureus

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“…In its current state, there is a need for manual supervision to ensure no improper content is introduced into LLM-created content, and it is not advisable to incorporate LLMs into a fully automated workflow. Some groups have voiced concerns that over-reliance on AI tools for pathology case sign-out may lead to deskilling, burnout, and diminished knowledge of the histology and mechanisms of disease [103,104]. Pathologists could end up using an AI tool to sign out a case without critically analyzing the case [105].…”

Section: Challenges and Limitationsmentioning

confidence: 99%

Applications of Large Language Models in Pathology

Cheng

2024

Bioengineering

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Large language models (LLMs) are transformer-based neural networks that can provide human-like responses to questions and instructions. LLMs can generate educational material, summarize text, extract structured data from free text, create reports, write programs, and potentially assist in case sign-out. LLMs combined with vision models can assist in interpreting histopathology images. LLMs have immense potential in transforming pathology practice and education, but these models are not infallible, so any artificial intelligence generated content must be verified with reputable sources. Caution must be exercised on how these models are integrated into clinical practice, as these models can produce hallucinations and incorrect results, and an over-reliance on artificial intelligence may lead to de-skilling and automation bias. This review paper provides a brief history of LLMs and highlights several use cases for LLMs in the field of pathology.

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