A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...

A machine learning model can predict hepatocellular carcinoma (HCC) risk using routinely available data, according to a study ...

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 ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a ...

If you’ve ever had a doctor order a blood test for you, chances are that they ran a complete blood count or CBC. One of the most common blood tests in the world, CBC tests are run billions of times ...

Routine blood samples, such as those taken daily at any hospital and tracked over time, could help predict the severity of an injury and even provide insights into mortality after spinal cord damage, ...

Researchers have built a machine-learning model that can distinguish between Alzheimer’s disease, dementia with Lewy bodies, ...

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.