A collaborative study between researchers at the Yong Lin Lin School of Medicine, National University of Singapore (Nus Medicine), and the Institute of Bioestadistics and Informatics in Medicine and Aging Research, Rostock University Medical Center, Germany, investigated how the tools of AI Advanced, as large language models (LLM), you can facilitate the evaluation of interventions for aging and provide personalized recommendations. The findings were published in the Leader Review Magazine Aged Research Reviews.
Research on aging is producing an overwhelming amount of data, which makes it difficult to determine what interventions, such as new medications, diet changes or exercise routines, are safe and effective. This study investigated how AI can analyze the data more efficiently and precisely, proposing an integral set of standards for AI systems to ensure that they deliver precise, reliable and understandable evaluations through their ability to analyze complex biological data.
The researchers identified eight critical requirements for effective IA:
- Accuracy of the results of the evaluation. Data quality will be evaluated by precision.
- Utility and amplitude.
- Interpretability and explanation of the results of the evaluation. Clarity and conciseness of the results and the explanations given.
- Specific consideration of causal mechanisms affected by the intervention.
- Data consideration in a Holistic context:
- Efficacy and toxicity, and evidence of the existence of a great therapeutic window;
- Analysis in an “interdisciplinary” configuration.
- Enabling reproducibility, standardizationand harmonization of the analysis (and the report).
- Specific emphasis on Various longitudinal data on a scale.
- Specific emphasis on the results related to known aging mechanisms.
Telling LLMS about these requirements as part of the application improved the quality of the recommendations they produced.
Professor Brian Kennedy of the Department of Biochemistry and Physiology, and the Healthy Longevity Translation Research Program in Nus Medicine, who led the study, said: “We tried artificial intelligence methods using real world examples such as medications and dietary supplements. We discovered We discover that we discover that we discover that we discover that we discover that we discover that we discover that we discover that we discover that we discover.
“The studies of the study could have long -range effects,” added Professor Georg Fuellen, director, Institute of Biostatistics and Informatics in Medicine and Aging Research, Rostock University Medical Center, who directed the study “, for medical care, which He told the AI about AI on AI. measure that age. “
In the future, the team is now focusing on a large -scale study of how to better boost AI models for longevity intervention councils, to evaluate their precision and reliability for a wide range of carefully designed reference points , that is, selected, high, high quality data. The validation of such AI systems is specifically important because longevity interventions can be implemented by a large number of healthy people. Prospective studies must demonstrate that IA -based evaluations can precisely predict successful results in humans, paving the way for safer and more effective health interventions.
The team hopes to use their findings to make health and longevity interventions more precise and accessible, and ultimately improve the quality and duration of life. The collaboration between researchers, doctors and policy formulators will be essential to establish robust regulatory frameworks, ensuring the safe and effective use of AI promoted evaluations.