Global AI in Epidemiology Market size is expected to be worth around USD 6,041.0 million by 2033 from USD 549.1 million in 2023.

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

Shillong: The department of information technology at North-Eastern Hill University (Nehu), Shillong, has developed an AI-based Landslide Susceptibili.

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

The Department of Information Technology at North-Eastern Hill University has developed a Landslide Susceptibility Map using ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

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

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

When infectious diseases surge, response often comes down to timing: whether communities can position the right people and supplies before case counts spike. A new tool developed by UC San Diego with ...

Abstract: This study explores the predictive capacity of financial asset returns in forecasting macroeconomic regime shifts, specifically the transition among Inflation, Expansion, Stagflation, and ...

Enterprise security faces a watershed as AI tools mature from passive analytics to autonomous operatives in both offense and defense. To date, traditional ...