AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...
Tech Xplore

Benchmarking framework reveals major safety risks of using AI in lab experiments

While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, ...
Multiple Sclerosis News Today

Machine learning model can predict PIRA in first years of MS diagnosis

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
IEEE

Diabetes Prediction using Different Machine Learning Classifiers

Abstract: Diabetes mellitus is a prevalent global health concern, necessitating proactive approaches for early detection and intervention. This paper explores the application of diverse machine ...
BMJ

Development and validation of a machine learning-based prediction model for frailty in older adults with diabetes: a study protocol for a retrospective cohort study

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...
Frontiers

A personalized prediction model for distinguishing between asymptomatic bacteriuria and symptomatic urinary tract infections in patients with type 2 diabetes mellitus using ...

Background: Patients with type 2 diabetes mellitus (T2DM) have an increased susceptibility to urinary tract infections (UTIs), caused by uropathogenic Escherichia coli (UPEC). Asymptomatic bacteriuria ...
Scientific Research Publishing

Breiman, L. (2001) Random Forests. Machine Learning, 45, 5-32.

ABSTRACT: Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and ...
Frontiers

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...