AIMED: AI for Prostate Cancer Detection and Immunotherapy Response
summary
Two EU-funded programs build a non‑invasive prostate screen around a urine vaporization device that produces spectral profiles with up to 6,000 omic features and a smartphone workflow, and a mechanistic immunotherapy platform that models cell electrical state using a Dublin “sear” engine and molecular graphs. A 1,357‑patient pilot shows detectable signal from urine; target clinical acceptance is ≥87% accuracy threshold. Models train via federated learning, and plans include in silico screening followed by in vitro and mouse double‑blind validation.
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chapters (9)
- 0:00AI in prostate cancer projects
- 1:05Motivation behind project
- 2:08Current detection challenges
- 7:05Noninvasive early detection approach
- 12:44Liquid biopsy and urine analysis
- 16:17Immunotherapy response modeling
- 18:46Multimodal data collection and SEAR platform
- 22:41Future project extensions
- 26:09Q&A
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