Abstract
Reverse vaccinology is an emerging concept in the field of vaccine development as it facilitates the identification of potential vaccine candidates. Biomedical research has been revolutionized with the recent innovations in Generative Artificial Intelligence (AI) and Large Language Models (LLMs). The intersection of these two technologies is explored in this study. In this study, the impact of Generative AI and LLMs in the field of vaccinology is explored. Through a comprehensive analysis of existing research, prospective use cases, and an experimental case study, this research highlights that LLMs and Generative AI have the potential to enhance the efficiency and accuracy of vaccine candidate identification. This work also discusses the ethical and privacy challenges, such as data consent and potential biases, raised by such applications that require careful consideration. This study paves the way for experts, researchers, and policymakers to further investigate the role and impact of Generative AI and LLM in vaccinology and medicine.
| Original language | English |
|---|---|
| Article number | 101533 |
| Journal | Informatics in Medicine Unlocked |
| Volume | 48 |
| DOIs | |
| Publication status | Published - Jan 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- AI
- AI ethics
- Generative AI
- Large language models (LLMs)
- Reverse vaccinology
- Vaccine candidate identification
- Vaccines
ASJC Scopus subject areas
- Software
- General Computer Science
- Information Systems
- Health Informatics
- Computer Science Applications
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