The intersection of artificial intelligence and mechanistic neuroscience is rapidly transforming our understanding of neural ...

When Hend Alqaderiwas studying how saliva could predict the risk of diabetes or the severity of a coronavirus infection, she collected a lot of saliva samples-thousands, measuring hundreds of bacteria ...

Sleep is one of medicine's underused data streams. Clinically, disturbed sleep has often been treated as a symptom of a disorder, but sleep is also a physiological state in which brain, cardiac, ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

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 ...

Feedback is excited to learn that University of Maryland researchers are measuring farts in a bid to build a Human Flatus ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

A research team from Juntendo University in Japan wanted to find a better way to predict survival for older people with heart failure. The project was led by Professor Tetsuya Takahashi, Assistant ...

Monitoring and treating heart failure (HF) is a challenging condition at any age. Several models, such as Atrial fibrillation, Hemoglobin, Elderly, Abnormal renal parameters, Diabetes mellitus (AHEAD) ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...