Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
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 identification to improve prevention and management strategies. Traditional risk ...

Oregon State University researchers use AI to predict freshwater fish species at risk of endangerment

Researchers at Oregon State University are using a tool to predict freshwater fish species at risk of endangerment, hoping to ...

Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models that are deeply aligned with their specific data domains ...
Science Friday

The Miniforest Movement Gains Ground In The U.S.

A 50-year-old planting method from Japan is jump-starting native forest ecosystems in small plots, from schoolyards to parking lots.
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 ...