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, ...

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 ...

Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

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) ...

Researchers from Odisha and Saudi Arabia have developed a hybrid AI model achieving 95.49% accuracy in predicting liver disease. This innovative tool, combining deep learning and boosting, promises ...

Abstract: Diabetes is one of the chronic diseases that causes blood sugar levels to rise. If diabetes is left untreated and undiagnosed, it can lead to complications. The time-consuming identification ...

For early identification and individualised management, machine learning-based diabetes prediction is essential. In this work, the methods for logistic regression (LR), naïve Bayes (NB), decision ...