A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Objectives To derive sex-specific peak oxygen uptake (VO 2peak) reference equations for cycle ergometer cardiopulmonary exercise testing (CPET) that integrate estimations of lean body mass (eLBM) and ...

This repository includes the training and evaluation code for the above paper. python train_script.py --name data_physics --data True --physics True --pretrained_checkpoint DATA_CHECKPOINT ...

The seven companies listed here cover the realistic range of what a buyer will encounter in 2026: embedded ML teams that own ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Mathematical Modeling is One of the Most Valuable Skills. Mathematical modeling is often associated with academic research, ...

Legacy R&D systems fragment data, limiting integration, collaboration and AI readiness across product development workflows.

The TabPFN tool, when combined with Geospatial Sparse Attention, works better on tabular geospatial data found in spreadsheets or databases.

Training deep learning models for semantic occupancy prediction is challenging due to factors such as a large number of occupancy cells, severe occlusion, limited visual cues, complicated driving ...

Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at ...