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By replacing repeated fine‑tuning with a dual‑memory system, MemAlign reduces the cost and instability of training LLM judges ...

Investigators sought to train and validate a machine learning model to distinguish paper mill publications from genuine articles and assess the prevalence of paper mill publications.

Introduction Mobile health (mHealth) technologies have become increasingly popular for monitoring mental health symptoms and lifestyle behaviours, and are largely reported to be feasible and ...

Abstract: In the present day, machine learning (ML), which is a subset of artificial intelligence (AI), has emerged as a crucial technology that has revolutionized the way in which we interact with ...

Deep-learning model decodes the regulatory effects of DNA changes ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Over the past year, I've been working on a challenge that faces every organization implementing Zero Trust: how do you manage ...

Think like a startup for innovation and agility, scale like an enterprise with systems and processes. Balance both approaches to drive sustainable growth.

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...

AI-powered penetration testing is an advanced approach to security testing that uses artificial intelligence, machine learning, and autonomous agents to simulate real-world cyberattacks, identify ...