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LARGE LANGUAGE MODELS (LLMS) AND CHATGPT FOR BIOMEDICINE
Cecilia Arighi1, Steven Brenner, Zhiyong Lu
1Department of Computer and Information Sciences, University of Delaware, Ammon-Pinizzotto, Biopharmaceutical Innovation Building, 590 Avenue 1743, Newark, DE19713, US†Work partially supported by NIH award U24 HG007822., arighi@udel.edu.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 31, 2023
Summary
Large Language Models (LLMs), a type of AI, are transforming biomedicine by analyzing data and generating content. This workshop explores their applications, innovations, and challenges in the biomedical field.
Area of Science:
- Biomedical Informatics
- Artificial Intelligence
- Natural Language Processing
Background:
- Large Language Models (LLMs) represent a significant advancement in artificial intelligence.
- LLMs possess advanced capabilities in processing, analyzing, and generating text-based data.
- Their application in biomedicine is rapidly expanding due to their potential to handle complex biological information.
Purpose of the Study:
- To provide a comprehensive overview of the emergence and impact of LLMs in the biomedical domain.
- To elucidate the innovative applications of LLMs in driving progress and enhancing outcomes within biomedical research and practice.
- To discuss the inherent challenges, limitations, and potential pitfalls associated with implementing LLMs in biomedicine.
Main Methods:
- Literature review of current LLM applications in biomedicine.
- Analysis of case studies showcasing LLM-driven innovations.
- Identification and discussion of ethical and technical challenges.
Main Results:
- LLMs are demonstrating transformative potential across various biomedical subfields.
- Key applications include drug discovery, clinical trial optimization, and personalized medicine.
- Significant challenges remain in data privacy, model interpretability, and regulatory compliance.
Conclusions:
- LLMs are poised to revolutionize biomedical research and healthcare delivery.
- Addressing challenges proactively is crucial for responsible and effective LLM integration.
- Continued research and development are essential to fully harness the benefits of LLMs in biomedicine.
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