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. 2024 Aug 31;65(2):E285-E289.
doi: 10.15167/2421-4248/jpmh2024.65.2.3261. eCollection 2024 Jun.

Perspectives on AI use in medicine: views of the Italian Society of Artificial Intelligence in Medicine

Francesco Andrea Causio  1   2 , Luigi DE Angelis  1   3 , Giacomo Diedenhofen  1   4 , Angelo Talio  1   5 , Francesco Baglivo  1   3 ; Workshop Participants
Collaborators, Affiliations

Perspectives on AI use in medicine: views of the Italian Society of Artificial Intelligence in Medicine

Francesco Andrea Causio et al. J Prev Med Hyg. .

Abstract

The first annual meeting of the Italian Society for Artificial Intelligence in Medicine (Società Italiana Intelligenza Artificiale in Medicina, SIIAM) on December 7, 2023, marked a significant milestone in integrating artificial intelligence (AI) into Italy's healthcare framework. This paper reports on the collaborative workshop conducted during this event, highlighting the collective efforts of 51 professionals from diverse fields including medicine, engineering, data science, and law. The interdisciplinary background of the participants played a crucial role in generating ideas for innovative AI solutions tailored to healthcare challenges. Central to the discussions were several AI applications aimed at improving patient care and streamlining healthcare processes. Notably, the use of Large Language Models (LLMs) in remote monitoring of chronic patients emerged as an area of focus. These models promise enhanced patient monitoring through detailed symptom checking and anomaly detection, thereby facilitating timely medical interventions. Another significant proposal involved employing LLMs to improve empathy in medical communication, addressing the challenges posed by cultural diversity and high-stress levels among healthcare professionals. Additionally, the development of Machine Learning algorithms for standardizing treatment in pediatric emergency departments was discussed, along with the need for educational initiatives to enhance AI adoption in rural healthcare settings. The workshop also explored using LLMs for efficient data extraction and analysis in scientific literature, interpreting healthcare norms, and streamlining hospital discharge records. This paper provides a comprehensive overview of the ideas and solutions proposed at the workshop, reflecting the participants' forward-thinking vision and the potential of AI to revolutionize healthcare.

Keywords: Artificial Intelligence; Large Language Models; Machine Learning; Workshop.

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Conflict of interest statement

The authors declare no conflict of interest.

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