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 ...

Approximately one in seven adults in the United States has kidney disease, where the organs responsible for filtering waste ...

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

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...

AI catches connections we miss. AI-IR was trained using independent cohorts from the United States and Taiwan, a collection of anonymized medical data ...

Insulin resistance—when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels—is ...

This repository consist of various machine learning models along with the dataset. The models are trained with widely used ML algorithms like Gradient Boost , Random Forest etc. Pickle is used to ...

Abstract: The recent AI development has provided effective solutions to address current problems and improve decision making process. The article takes a case study in Data and Information Centre ...

1 School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu, China. 2 Guyuan Meteorological Bureau, Guyuan, China. 3 Jilin Provincial Institute of Meteorological ...

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...