Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.
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A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
For its 2nd anniversary, Callisto DataHub offers free annotated datasets of 50 suspected lung cancer X-rays and 50 ...
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
The IAEA is inviting research organizations to join a new project that will use machine learning to better predict structural changes in polymers caused by ionizing radiation. Rad ...
Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
The integration of imaging and artificial intelligence has radically transformed the landscape of radiotherapy, positioning advanced imaging modalities such ...
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