Scientific Research Publishing

Analysis of Decision Support Systems (DSS) Integration with AI Using Mobile Health (m-Health) and Wearables ()

Smart health refers to the integration of cutting-edge technologies into healthcare systems to improve patient care and apply ...
GitHub

Heart Disease Classification using Machine Learning Algorithms (SVM, MLP, Random Forest) for Medical Diagnosis

There was an error while loading. Please reload this page. This project focuses on developing and evaluating machine learning models to classify individuals into ...
BMJ

Development and validation of a machine learning-based prediction model for frailty in older adults with diabetes: a study protocol for a retrospective cohort study

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...
Frontiers

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...
Scientific Research Publishing

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

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...
Frontiers

A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021)

Background: Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical settings where fundus cameras are not accessible.
IEEE

Diabetes Prediction Using Machine Learning Algorithm: A Comparative Analysis

Abstract: Diabetes prediction is an essential task in healthcare that could be achieved through Machine Learning models. Several factors contribute to diabetes such as overweight, high cholesterol ...
IEEE

Diabetes Prediction using Support Vector Machine, Naive Bayes and Random Forest Machine Learning Models

Abstract: Nowadays, diabetes is a relatively prevalent condition. This illness affects a large number of people worldwide. Numerous renal and cardiac disorders are mostly caused by diabetes. The major ...