AZoOptics

AI-Enhanced Optical Spectroscopy for On-Line Food Quality Monitoring

AI-enhanced optical spectroscopy revolutionizes food quality monitoring with rapid, non-destructive analysis, ensuring safety and reducing waste in production.
News-Medical.Net

Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
Analytics Insight

Explore Data Science This Weekend: Best YouTube Channels to Follow

Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...
Scientific Research Publishing

The Grover Dilemma and Three Fundamental Barriers to Oracle-Based Quantum Search Algorithms ()

Those that solve artificially simplified problems where quantum advantage is meaningless. Those that provide no genuine quantum advantage when all costs are properly accounted for. This critique is ...
Devdiscourse

Next-gen AI biosensors promise faster, smarter pandemic surveillance

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
IEEE

Soil Moisture Estimation From Spire GNSS-Reflectometry Reflectivity: Semi-Empirical and Linear Regression Methods

Abstract: This study develops semi-empirical and linear regression algorithms to estimate near-surface soil moisture (SM) using reflectivity observations of Global Navigation Satellite System ...
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 ...

Machine learning for machines This tyre factory’s efficiency soars

Sensors, computer vision models, and artificial intelligence have combined to help CEAT Tyres’ Chennai factory reduce defects, waste and energy use, a.
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 ...
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 ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...