FrontlineOpinion

The governing vision of the class must rest with a human teacher: Saikat Majumdar

As AI transforms learning and work, Saikat Majumdar argues ethics, inequality, and human relationships—not technical skills ...

Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
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 ...
Tech Xplore

Combining lessons from ants and birds to improve AI

Combining ideas inspired by ant colonies and flocks of birds may hold the key to unlocking more effective artificial ...
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 ...
AOL

What Does BTS Mean? All About the Beloved K-Pop Group's Unique Moniker

BTS attend 2021 AMERICAN MUSIC AWARDS - The AMAs will air live from the Microsoft Theater in Los Angeles on Sunday, Nov. 21 Credit: ABC via Getty Since releasing their first album in 2013, BTS has ...
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, ...
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 ...