A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Heat stress is widely recognized as a critical risk factor in livestock systems. Rising temperatures and humidity levels can ...
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.
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
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 ...
Using longitudinal data on more than 370 000 older Japanese adults, we found that living in constituencies represented by pro-tobacco legislators was associated with higher smoking prevalence. The ...
Data is the life-blood of physical AI. Collecting real-life data is expensive. Generative AI and diffusion to create ...
Background Gut microbiota dysbiosis is linked to autism spectrum disorder (ASD) in children. However, the role of bacterial ...
Whether it's redfin pickerel in the Kennebec River or sturgeon in the Great Lakes, nearly one-third of freshwater fish ...
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