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 ...

The explosion in data quantity has kept the marriage of computing and statistics thriving through successive hype cycles: “big data,” “data science,” and now “AI.” ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Background: Middle-aged and older endurance athletes have increased prevalence of coronary artery disease (CAD) on coronary CT angiography (CCTA) compared to healthy controls, despite similarly low ...

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 ...

By Priyanjana Pramanik, MSc. A large European study shows that clubs systematically discount players with higher predicted ...

Explore how AI-powered forensic data audits can enhance data literacy and improve air quality measurements for socio-economic ...

By Hugo Francisco de Souza A large US trial shows that the cumulative burden of alcohol over decades matters for colorectal ...

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 ...

Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...

Aims The obesity paradox has been described in different cardiovascular conditions. Data on the association between obesity and outcomes in patients with Takotsubo syndrome (TTS) are lacking. The aim ...