Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Psychology Today

AI Foundation Model Predicts Diseases From Brain Scans

Breakthrough AI foundation model called BrainIAC is able to predict brain age, dementia, time-to-stroke, and brain cancer ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
News-Medical.Net

Implantable immune scaffold predicts type 1 diabetes weeks before symptoms

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

Data-driven AI approach narrows diagnostic gap between dengue and chikungunya

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

RFX-Fuse: Breiman and Cutler's Random Forests as a Forest Unified Learning and Similarity Engine - Extended with Native Explainable Similarity

RFX-Fuse (Random Forests X [X=compression] — Forest Unified Learning and Similarity Engine) delivers Breiman and Cutler's complete vision for Random Forests as a Forests Unified Machine Learning and ...
AZoRobotics

Using Deep Learning to Predict Disease Progression in Chronic Illnesses

Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...
European Medical Journal

AI Predicts Cardiometabolic Multimorbidity Risk in Type 2 Diabetes

Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.
Oak Ridge National Lab

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial ...
Frontiers

Multi-feature integrated machine learning prediction model for early nephropathy in elderly living with type 2 diabetes mellitus

Aims: To develop and validate a multi-feature machine learning (ML) model for early diabetic nephropathy (DN) prediction in elderly living with type 2 diabetes mellitus (T2DM), incorporating clinical ...
IEEE

A Comparative Analysis of Machine Learning Algorithms for Diabetes Prediction Using Numerical-to-Image Data Transformation

Abstract: Diabetes is a global health issue that requiring early detection to prevent life-threatening complications. This study compares several machine learning models for predicting diabetes using ...