The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Aaron Y. Lee, MD, MSCI, explains how temporal optical coherence tomography modeling may improve longitudinal disease tracking and clinical decision-making.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

SpaceX uses your data to train its machine learning and AI models and might share that with partners who 'help us develop AI-enabled tools that improve your customer experience.' From the laptops on ...

California’s AB 2013, also known as the Generative Artificial Intelligence: Training Data Transparency Act (TDTA), took effect on January 1, 2026. In our June 2025 alert, “California’s AB 2013: ...

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...

A type of cognitive training that tests people's quick recall seems to reduce the risk of dementia, including Alzheimer's disease ...