A study on CHARTwatch reveals its effectiveness in predicting patient deterioration, leading to reduced non-palliative care mortality in general medicine units.

One of the most common blood tests in the world, CBC tests are run billions of times each year, can be imprecise. Experts are turning to machine learning to change that.

In a newly published research, scientists used machine learning to identify healthy blood count ranges for individual patients and predict their risk of future disease.

Using machine learning models, we predicted interim positron emission tomography-computerized tomography by using changes in blood test results in pediatric patients with classical Hodgkin lymphoma in ...

Lab tests are interpreted based on reference intervals. Defining what’s normal for you Luckily, many patients get blood counts each year as part of routine checkups. Using machine learning ...

Blood tests are currently one-size-fits-all − machine learning can pinpoint what's truly 'normal' for each patient Many people commonly think of clinical tests as purely diagnostic.