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Multi-organ Biological Age Reveals Causal Relationships Between Human Aging, Disease, & Lifestyle Factors

Wed, Oct 02

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Virtual Event

This presentation will cover the following points: 1) Introduction of recent research on multi-organ biological age gaps using machine learning; 2) Use of multimodal biomedical data and genetic data as instruments to analyze the associations and causal relationships between human aging and disease

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Multi-organ Biological Age Reveals Causal Relationships Between Human Aging, Disease, & Lifestyle Factors
Multi-organ Biological Age Reveals Causal Relationships Between Human Aging, Disease, & Lifestyle Factors

Time & Location

Oct 02, 2024, 10:00 a.m. PDT

Virtual Event

Guests

About the event

Topic: Multi-organ Biological Age Reveals Causal Relationships Between Human Aging, Disease, and Lifestyle Factors

Time: October 2, 2024 10:00AM Pacific Time / October 2, 2024 13:00PM EDT / October 2, 2024 19:00PM CEST / October 3, 2024 01:00AM CST (other timezones)

The detailed Zoom meeting information will be provided in the email upon completion of your registration with your email address.

Speaker: Dr. Junhao (Hao) Wen

Dr. Wen is the principal investigator of the LABS (https://labs-laboratory.com/) at the University of Southern California.

Dr. Wen’s research endeavors focus on developing and applying artificial intelligence and machine learning (AI/ML) techniques to analyze multi-organ, multi-omics biomedical data for studying human aging and disease. His research endeavors include scrutinizing the reproducibility of AI/ML in neuroimaging research, depicting the neuroanatomical heterogeneity of brain disorders using AI/ML and imaging genetics, and embracing multiscale approaches to investigate human aging and disease. In this talk, he will introduce his recent research results on multi-organ biological age gaps (BAGs) derived through machine learning. Specifically, he will introduce how to use multimodal biomedical data and genetic data as instruments to analyze the associations and causal relationships between human aging and disease.

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