NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

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 ...

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...

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 ...

The video game industry has evolved leaps and bounds over the last half century, from simple arcade-like gameplay to highly immersive, intelligent, and interactive gaming. With advancements in ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Abstract: This study proposed an effective machine learning (ML)-based fault diagnosis method for demagnetization faults, including “healthy, 30% unipolar demagnetization, 50% multimagnet ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...