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Deep Learning for Body Composition in Pediatric Lymphoma

Deep Learning for Body Composition in Pediatric Lymphoma

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Featured paper: Deep learning of image‑derived measures of body composition in pediatric, adolescent, and young adult lymphoma: association with late treatment effects
Can AI predict which young cancer patients will face serious complications years after treatment? In this episode, we explore groundbreaking research that uses deep learning to analyze body composition from routine CT scans in pediatric lymphoma patients. Discover how this AI technology can measure muscle and fat changes in under one second—work that would take humans hours—and why losing just 11.5% of muscle mass during treatment dramatically increases future health risks. Join us as we uncover how this "super-powered internal GPS" is paving the way for truly personalized cancer care, helping doctors identify high-risk patients early and tailor treatment plans to ensure young survivors emerge not just cancer-free, but healthier and stronger for the future.*Disclaimer: This content was generated by NotebookLM and has been reviewed for accuracy by Dr. Tram.*
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