Pharmacy professor develops AI model to predict hospitalization of at-risk cardiac patients

When Arinze Nkemdirim Okere, PharmD, MBA, worked as the pharmacist for a hospital in Tallahassee, Florida, he noticed that ...
Ministry of Testing

The future of testing: Autonomous agents, ethical AI, and human oversight

Understand why testing must evolve beyond deterministic checks to assess fairness, accountability, resilience and ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
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 ...
Hosted on MSN

Logistic Regression in Machine Learning Explained with a Simple Example

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Hosted on MSN

Linear Regression Cost Function | Machine Learning | Explained Simply

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...
Frontiers

Regression-based machine learning models for nitrate and chloride prediction in surface water in a small agricultural sand plain sub-watershed in southwestern Ontario, Canada

Machine learning (ML) models have proven to be an efficient technique for better understanding and quantification of surface water quality, especially in agricultural watersheds where considerable ...
IEEE

Systematic Bias of Machine Learning Regression Models and Correction

Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large-valued ...