Artificial intelligence in biology and medicine, and radioprotection research: perspectives from Jerusalem

• Published in: Frontiers in artificial intelligence Vol. 6; p. 1291136
• Main Authors: Socol, Yehoshua, Richardson, Ariella, Garali-Zineddine, Imene, Grison, Stephane, Vares, Guillaume, Klokov, Dmitry
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 11.01.2024
• Subjects: artificial intelligence; ionizing radiation; Life Sciences; low doses; machine learning; public health; radioprotection; radioprotection; machine learning; low doses; artificial intelligence; ionizing radiation; public health
• ISSN: 2624-8212; 2624-8212
• DOI: 10.3389/frai.2023.1291136

While AI is widely used in biomedical research and medical practice, its use is constrained to few specific practical areas, e.g., radiomics. Participants of the workshop on "Artificial Intelligence in Biology and Medicine" (Jerusalem, Feb 14-15, 2023), both researchers and practitioners, aimed to build a holistic picture by exploring AI advancements, challenges and perspectives, as well as to suggest new fields for AI applications. Presentations showcased the potential of large language models (LLMs) in generating molecular structures, predicting protein-ligand interactions, and promoting democratization of AI development. Ethical concerns in medical decision making were also addressed. In biological applications, AI integration of multi-omics and clinical data elucidated the health relevant effects of low doses of ionizing radiation. Bayesian latent modeling identified statistical associations between unobserved variables. Medical applications highlighted liquid biopsy methods for non-invasive diagnostics, routine laboratory tests to identify overlooked illnesses, and AI's role in oral and maxillofacial imaging. Explainable AI and diverse image processing tools improved diagnostics, while text classification detected anorexic behavior in blog posts. The workshop fostered knowledge sharing, discussions, and emphasized the need for further AI development in radioprotection research in support of emerging public health issues. The organizers plan to continue the initiative as an annual event, promoting collaboration and addressing issues and perspectives in AI applications with a focus on low-dose radioprotection research. Researchers involved in radioprotection research and experts in relevant public policy domains are invited to explore the utility of AI in low-dose radiation research at the next workshop.