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A multi-omics joint detection system for prostate cancer recurrence risk assessment

PendingCN122266773Aavoid lossReally restore spatial heterogeneityMedical simulationMedical data miningProstate cancerRecurrence prediction
The application provides a multi-omics joint detection system for prostate cancer recurrence risk assessment, the application synchronously acquires genomic, transcriptomic, epiproteomic and metabolomic data of different regions of a tumor through spatially resolved in situ capture technology, and integrates multi-dimensional information such as circulating tumor DNA epigenetic memory, urological microbiome-host interaction, single-cell clone evolution and tumor microenvironment three-dimensional topology. The system uses a dynamic Bayesian fusion engine to perform probabilistic risk calculation, combines digital twin technology to simulate treatment response, and realizes model adaptive updating through longitudinal follow-up data. The output result has high interpretability and can directly show key driving factors and their clinical interventional properties. The system breaks through the limitations of traditional static and single-omics models, significantly improves the prediction accuracy of recurrence, especially in low-risk populations, and provides intelligent support for individualized auxiliary treatment decisions.
Owner:湖南医药学院

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