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Accepted for/Published in: JMIR Bioinformatics and Biotechnology

Date Submitted: Sep 12, 2023
Date Accepted: Apr 17, 2024

The final, peer-reviewed published version of this preprint can be found here:

ChatGPT and Medicine: Together We Embrace the AI Renaissance

Hacking S

ChatGPT and Medicine: Together We Embrace the AI Renaissance

JMIR Bioinform Biotech 2024;5:e52700

DOI: 10.2196/52700

PMID: 38935938

PMCID: 11135232

ChatGPT and Medicine - Together We Embrace the AI Renaissance

  • Sean Hacking

ABSTRACT

This editorial paper explores the transformative potential of the generative artificial intelligence (AI) model, Chat Generative Pre-training Transformer (ChatGPT) in the fields of bioinformatics, biotechnology, and medicine, presenting perspectives from both the AI and the physician. The development of such models has signaled the beginning of a new era where complex biological data can be made more accessible and interpretable. ChatGPT is a natural language processing tool with the ability to process, interpret, and summarize vast datasets. It can serve as a digital assistant for physicians and researchers, aiding in the integration of medical imaging data, multi-omics data, identifying patterns in genomic variations, and facilitating the understanding of complex biological systems. Notably, its potential contribution to the field of cancer genomics and precision medicine is discussed. The physician's and the AI’s viewpoint emphasize the value of such AI models in a clinical setting, providing tangible examples of how this could enhance patient care and treatment strategies. The editorial also discusses the rise of generative AI, highlighting its significant impact in democratizing bioinformatics applications for modern medicine. While AI may not supersede healthcare professionals, practitioners incorporating AI into their practices could potentially have a competitive edge.


 Citation

Please cite as:

Hacking S

ChatGPT and Medicine: Together We Embrace the AI Renaissance

JMIR Bioinform Biotech 2024;5:e52700

DOI: 10.2196/52700

PMID: 38935938

PMCID: 11135232

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