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 ...
IEEE

Predictive Analytics in Mental Health: Machine Learning Models for Major Depressive Disorder Detection using Sensor Data

Abstract: The recent integration of Machine Learning (ML) and sensor technologies in healthcare, particularly for diagnosing Major Depressive Disorder (MDD), has paved the way for advanced predictive ...
Analytics Insight

Top Data Science Projects to Boost Your Resume in 2026

Overview:Practical projects can help you showcase technical skill, programming knowledge, and business awareness during the hiring process.Designing end-to-end ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Sophelio Launches Data Fusion Labeler (dFL) to Accelerate Sensor Data Preparation for Machine Learning

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...
IEEE

Corrections to “Chronic Diseases Prediction Using Machine Learning With Data Preprocessing Handling: A Critical Review”

Abstract: Presents corrections to the paper, (Corrections to “Chronic Diseases Prediction Using Machine Learning With Data Preprocessing Handling: A Critical Review”).