Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Frontiers

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
Scientific Research Publishing

Breiman, L. (2001) Random Forests. Machine Learning, 45, 5-32.

ABSTRACT: Accurate land cover classification is essential for environmental monitoring, urban planning, and resource management. Conventional classifiers trained on raw spectral bands are often ...
IEEE

Heart Disease Prediction Using Random Forest in Machine Learning Using The Concepts of Data Mining

Abstract: Heart disease remains one of the leading causes of death worldwide, making early prediction essential for treatment and prevention. This study applies machine learning techniques, ...
IEEE

Heart Disease Identification Using Machine Learning Algorithm

Abstract: After all advancements in technology and times, prediction and prevention of heart diseases is still a major issue in modern days. Heart diseases play a major role in high death rate in ...
SciELO

Predicting compressive strength of concrete with fly ash, metakaolin and silica fume by using machine learning techniques

The compressive strength (CS) is the most important parameter in the design codes of reinforced concrete structures. The development of simple mathematical equations for the prediction of CS of ...