AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

An AI-driven computational toolkit, Gcoupler, integrates ligand design, statistical modeling, and graph neural networks to predict endogenous metabolites that allosterically modulate the GPCR–Gα ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Introduction Prescribing high-dose antipsychotics is typically reserved for individuals with treatment-resistant severe ...

Two-photon imaging and ocular dominance mapping. A. Optical windows for imaging of two macaques. Green crosses indicate the regions for viral vector injections, and yell ...

Objective To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Researchers at Thomas Jefferson University have developed an automated machine learning (AutoML) model that can accurately ...

Giuseppe De Palo of JAMS explores how mediation can adapt to resolve disputes arising from algorithmic hiring systems without ...

Researchers at Thomas Jefferson University have developed a groundbreaking automated machine learning (AutoML) model that can accurately differentiate between two common types of brain tumors using ...

As of the November 25, 2025 data cutoff in the open-label Phase 2 portion of TUPELO, treatment with REC-4881 (4 mg QD) ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...