The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

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 ...

Free’ delivery is just a clever psychological illusion. The cost is rarely eliminated; it is simply redistributed into higher ...

Abstract: This study intends to use a gradient boosting machine to estimate the laser welding quality of copper/glass junctions based on the experimental data. Two output characteristics, such as seam ...

Sensors, computer vision models, and artificial intelligence have combined to help CEAT Tyres’ Chennai factory reduce defects, waste and energy use, a.

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Recently, we had the opportunity to exchange ideas on smart city initiatives in Singapore and we anticipated a focus on technologies such as AI and digital twinning, where the country excels. What ...