Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

University of Warwick research warns that popular deep learning systems trained for cancer pathology may be relying on hidden ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

Researchers used AI and deep learning to find a link between brain structure and navigation skills but found no measurable ...