IEEE

Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things

Abstract: In the Internet of Things, information fusion is among the crucial problems and probably occurs due to the dense deployment of consumer electronic devices. In the literature, various ...
The New York Times

Google’s Quantum Computer Makes a Big Technical Leap

Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...
GitHub

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

This project demonstrates the application of various machine learning algorithms for heart disease classification. By comparing the performance of SVM, MLP, and Random Forest models, we can determine ...
Assembly Mag

Traditional Machine Learning for Practical Machine Vision: It’s Been There All Along

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...
Frontiers

Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...
Scientific Research Publishing

Hybrid Software Model for Defect Detection and Cost Evaluation Using Support Vector Machine Algorithm ()

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
BMJ

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
Scientific Research Publishing

Machine Learning-Based Classification of Coronary Heart Disease: A Comparative Analysis of Logistic Regression, Random Forest, and Support Vector Machine Models ()

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...
IEEE

Implementation and Performance Evaluation of Machine Learning-Based Apriori Algorithm to Detect Non-Technical Losses in Distribution Systems

Abstract: The emergence and augmentation of nontechnical losses (NTLs) in a power distribution system has always been considered a critical issue in the global electricity market. Being considered as ...