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 ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Discover how AI and machine learning are transforming electric utilities—boosting grid reliability, resilience, and ...

QSR brands have increasingly turned to mobile apps to engage with their customers. From McDonald's notorious deals exclusive to app users to Starbucks rewards for in-app purchases, fast food companies ...

In the fiercely competitive fast-moving consumer goods (FMCG) sector, brand visibility is crucial. Consumers' purchasing decisions are increasingly influenced by their online search behaviors, making ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

Please provide your email address to receive an email when new articles are posted on . The model, along with a traffic-light system, boosted sensitivity and specificity of agitation recognition.

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...