Devdiscourse

AI models face real-world reality check in 6G network slicing

One of the key findings is that raw accuracy in laboratory conditions does not guarantee stability in deployment. The study ...
Devdiscourse

Big data adoption surges across industries but governance gaps persist

Real-time data processing has become essential as organizations demand faster insights. Integration with artificial intelligence and machine learning has expanded predictive capabilities, while edge ...
RMD Open

Systemic lupus erythematosus damage risk index (SLE-DRI): a simple machine learning-based tool for identifying patients at risk for early organ damage

Objective Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE).
Endovascular Today

Artificial Intelligence to Predict Outcomes in Peripheral Artery Disease

AI applications are a promising solution for PAD that may translate into earlier detection, customized risk assessment, and improved outcomes.

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to cleaning ingredients (handling missing values, standardization) Model ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

RIT computing students and Professor Rui Li are working on a National Institutes of Health-funded project to use AI in ...
Visual Studio Magazine

Linear Regression with Two-Way Interactions Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...