A new project at Purdue University that combines many types of available data in a “digital twin” model of bladder cancer may prove powerful enough to predict patient outcomes.
AZoM on MSN3d
New 3D Model for Gastric Cancer ResearchA novel 3D bioprinted gastric cancer model using patient-derived tissues predicts drug responses, enhancing personalized ...
A collaborative research team led by Professor Jinah Jang from the Department of Mechanical Engineering and the Department of ...
A collaborative research team from POSTECH has successfully developed a gastric cancer model using 3D bioprinting technology ...
Using preoperative chest CT scans, researchers identified novel preoperative biomarkers for lung cancer recurrence ...
Cancer models developed with 3D bioprinting technology allow for rapid evaluation of individual drug responses.
the model significantly improves prediction accuracy for cancer driver genes. This advancement enables more precise identification of genes closely associated with cancer progression, which is ...
Beyond improving accuracy, xAI allowed researchers to compare prognostic markers across different cancer types, unveiling ...
Laboratory for Research on the Structure of Matter (LRSM), University of Pennsylvania, Philadelphia, United States ...
News Medical on MSN4d
AI-driven ECG age prediction transforms early disease detectionAI-enabled ECG biological age (ECG-BA) improves disease risk classification beyond chronological age, enhancing early ...
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