Cancer immunotherapy drugs known as immune checkpoint inhibitors (ICIs) can be miracle drugs for cancer patients, curing some and turning deadly disease into a manageable chronic condition in others.

A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

Abstract: Cardiovascular diseases (heart diseases) are the leading cause of death worldwide. The earlier they can be predicted and classified; the more lives can be saved. Electrocardiogram (ECG) is a ...

Computational point-of-care sensors can significantly improve access to diagnostics by enabling rapid patient testing outside centralized medical facilities. These tests rely on machine learning ...

Abstract: Health information technology is one of today’s fastest-growing and most powerful technologies. This technology is used predominantly for predicting illness and obtaining medications quickly ...

A recent Nature Medicine study developed and validated OBSCORE, a model that identifies obese or overweight individuals who are most likely to develop related health problems. Obesity represents a ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in millions of patients with obstructive sleep apnea, a serious sleep disorder ...

Researchers developed and externally validated a machine learning model to predict the 28-day mortality risk in ICU patients with sepsis complicated by acute respiratory failure. Using routinely ...

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 human brain is complex. Artificial intelligence (AI) machine learning and medical imaging data are accelerating breakthroughs in brain health, especially in medical diagnostics. A peer-reviewed ...

A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...