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 ...
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 ...
emjreviews.com

AI Models Combine Genomics and Demographics to Predict Gastric Cancer Risk

NEW research suggests that integrating pathogen genomics with patient demographic data using supervised machine learning can substantially improve prediction of gastric cancer risk in people infected ...
Physicians Committee

AI-Driven “Patient Avatars” Aim to Replace Animal Testing and Predict Drug Toxicity

Study in a Sentence: Cedars-Sinai researchers are developing KronosRx, an artificial intelligence-powered platform that uses human-derived organoids and deep-learning models to forecast adverse drug ...
Scandasia.com

Reducing Regression Testing Time Without Sacrificing Quality

In today’s fast-paced software development landscape, speed and quality are equally critical. Development teams face constant pressure to release updates quickly, yet rushing releases without thorough ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Hosted on MSN

Build logistic regression in Python from scratch easily

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
marktechpost

Can a Small Language Model Predict Kernel Latency, Memory, and Model Accuracy from Code? A New Regression Language Model (RLM) Says Yes

Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...