Quantum reservoir computing peaks at the edge of many-body chaos, study suggests

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
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 ...
Medindia

Machine Learning Tool Predicts Post-Transplant Complications

BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...

Enterprises achieve 50% faster testing cycles with AI-driven autonomous quality assurance

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.
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 ...
Visual Studio Magazine

Decision Tree Regression from Scratch Without Pointers or Recursion Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...
Nanowerk

When machine learning shows its reasoning, electrocatalyst discovery accelerates

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
North Penn Now

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 ...
IEEE

Federated Function-on-function Regression with an Efficient Gradient Boosting Algorithm for Privacy-Preserving Telemedicine

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...