IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...

Understanding Homoskedasticity in Regression Modeling With Examples

Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.
Yehey.com

Yehey.com - UNT Introduces New AI Major to Meet Growing Workforce Demand

Image courtesy by QUE.com The University of North Texas (UNT) is stepping into the future with a new undergraduate major in ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
InfoQ

Microsoft Agent Framework RC Simplifies Agentic Development in .NET and Python

Microsoft has announced that the Microsoft Agent Framework has reached Release Candidate status for both .NET and Python. This milestone indicates that the API surface is stable and feature-complete ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Clinically informed AI outperforms foundation models in spinal cord disease prediction

Cervical spondylotic myelopathy (CSM) refers to spinal cord compression from arthritis in the neck and is the leading cause of spinal cord dysfunction in older adults. CSM is a chronic, progressive ...
IEEE

Harnessing Machine Learning for Intelligent Networking in 5G Technology and Beyond: Advancements, Applications and Challenges

Abstract: A revolutionary age in telecommunications is being ushered in by the confluence of machine learning (ML) with fifth-generation (5G) wireless communication technologies and beyond. This ...
Psychology Today

Diagnosing Schizophrenia With Machine Learning

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
Dot Physics on MSN

Building an elastic collision simulator with springs in Python

Building an elastic collision simulator with springs in Python to model realistic physics interactions and dynamic object collisions. Learn how to implement spring forces, momentum conservation, and ...
BMJ Open

Association between maternal age at childbirth and children’s internalising problems in the USA: a cross-sectional mediation analysis of housing instability and family ...

Objectives The optimal maternal age at childbirth has been a topic of bourgeoning literature, with earlier ages offering physiological benefits for maternal recovery. In contrast, later ages to give ...
Analytics Insight

Best Machine Learning Bootcamps in 2026 to Start Your AI Career

Overview:Machine learning bootcamps focus on deployment workflows and project-based learning outcomes.IIT and global programs provide flexible formats for appli ...