Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...

Financial word of the day: Heteroscedasticity describes a situation where risk (variance) changes with the level of a ...

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

Series B and C start-ups are evaluated across three main areas: financial performance, funding and valuation and operational capabilities ...

Harshith Kumar Pedarla explores using GANs to simulate network attacks. Synthetic data augmentation improves detection scores ...

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 ...

The study highlights a presymptomatic phase in type 1 diabetes progression, using immune niches to track immune changes ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

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 ...