New Scientist

Quantum neural network may be able to cheat the uncertainty principle

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

NITK uses machine learning to predict landslides in Western Ghats

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
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 ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

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

Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm

1 Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China 2 Mental Health Center, University-Town Hospital of Chongqing Medical University, Chongqing, ...
labs.sogeti

MACHINE LEARNING ALGORITHMS FOR TEST AUTOMATION

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 ...
IEEE

Diagnosis of Demagnetization Faults in PMSGs Based on Performance Evaluation of Machine Learning Algorithms Through Flux and Current Signals

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