Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...

A chest-worn biosensor that features several measurement signals in one device reliably identifies the presence and severity ...

The deep learning model developed by researchers at the University of Pennsylvania identified severe heart dysfunction far ...

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 patient’s risk of hepatocellular carcinoma (HCC), the most common ...

Francesco Perono Cacciafoco received funding from Xi'an Jiaotong-Liverpool University (XJTLU): SURF Grant "Unveiling the Secrets of the Singapore Stone: A Digital Philology Investigation" - Grant ...

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...

The integration of male sex, right bundle branch block (RBBB), and haemoglobin and glucose levels with the HEART (history, ECG, age, risk factors, and troponin levels) score enhanced its ability to ...

Heart disease can be silent, but what if your body sends signals — other than overt symptoms like chest pain — that you’re at risk? One potential sign is right on the side of your head. It takes just ...

Abstract: The heart plays a pivotal role in the functioning of living organisms, making its diagnosis and prediction of related diseases a matter of utmost importance. Approximately 17.9 million ...

A Michigan health system is turning to AI to help identify patients at risk of cardiovascular disease, without those patients needing to come in for additional testing. McLaren Health Care plans to ...