In the latest PennAITech webinar, sponsored by the National Institute on Aging, we were privileged to hear from Dr. Constantin Aliferis, a distinguished professor and director at the University of Minnesota, where he leads several major informatics initiatives. During his presentation on "Best Practices for Safe & Effective AI and ML; Select Case Studies from Aging & Longevity Research," Dr. Aliferis provided a comprehensive overview of the application of AI and machine learning in biomedical research. He emphasized the critical importance of developing robust, reliable AI systems to enhance the quality and efficacy of health interventions, particularly in aging and longevity research. Dr. Aliferis shared insights from his extensive research and recent book, highlighting the common pitfalls in AI application and underscoring the need for high-dimensional modeling to transform biomedical data into actionable knowledge. Key takeaways included the necessity for stringent best practices in AI and ML to avoid common errors and enhance the safety and effectiveness of these technologies in real-world health applications.

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