Thorax

Performance of multivariable risk prediction algorithms in predicting COPD exacerbations: a population-based study

Introduction Efficient preventive management of acute exacerbation of chronic obstructive pulmonary disease (COPD) is ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
TechCrunch

A satellite just learned to find things on its own — here’s what that means

For the first time, an Earth observation satellite has found what it was looking for — on its own, without human analysts on the ground. The milestone, which occurred in April, marks the first ...
IEEE

AML-K: An Analog Machine Learning Accelerator for K-Means at the Edge with Hardware-Software Co-Optimization

Abstract: Healthcare and wellness applications often require always-on, real-time processing under strict power and area constraints, particularly in wearable devices. Among various machine learning ...
LinkedIn

Clustering in Machine Learning: Types, Algorithms & Key Methods Explained

Clustering stands as one of the foundational concepts in machine learning. It enables systems to automatically organize similar data points into meaningful groups — all without requiring labeled ...
The New York Times

Where Have All the Book Reviews Gone?

What the rise of A.I. and the gutting of books coverage across U.S. media will mean for literature. By Dwight Garner In 1981, Donald Barthelme published “Challenge,” a funny and weirdly prescient ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
LinkedIn

K-Means Clustering Explained: A Beginner Guide from the Best Machine Learning Course in Chandigarh

This blog is specially designed for students, freshers, IT beginners, working professionals, and even non-IT learners who want to upgrade their skills. At the end, you will also learn how Netmax ...
The New York Times

What A.I. Really Means for Learning

A.I. is fueling a “poverty of imagination.” Here’s how we can fix it. By Meher AhmadJessica Grose and Tressie McMillan Cottom Produced by Vishakha Darbha Artificial intelligence is already showing up ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...