The Banker

Banks and regulators clash over ‘black box’ AI credit risk

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...
Frontiers

Non-invasive prediction of detrusor underactivity in benign prostatic hyperplasia: an interpretable machine learning framework to optimize surgical selection

This retrospective cohort study enrolled 538 urodynamically evaluated BPH patients. A rigorous multidimensional feature selection pipeline (LASSO, Boruta, and Recursive Feature Elimination) distilled ...
Ggwash.org

How I used friendly neighborhood data science to advocate for housing in Arlington

Above the RiverHouse neighborhood in Pentagon City. Image by Arlington County/JBG Smith. Last year, a long-discussed proposal for adding hundreds more housing units to the RiverHouse apartment complex ...
LinkedIn

XGBoost: The Powerhouse Behind Winning Machine Learning Models

In the world of Machine Learning, where accuracy, speed, and scalability define success, XGBoost (Extreme Gradient Boosting) has emerged as a game-changing algorithm. From Kaggle competitions to ...
Nature

Estimation and optimization of reinforcement parameters for composite material using a machine learning approach

The mechanical properties of Metal Powder Reinforced Polymer Matrix (MPRPM) composite materials are significantly influenced by various reinforcement parameters, such as the particle size of the ...
Medical Xpress

AI algorithm to more effectively research maternal-child health

A mother's health during pregnancy, childbirth and the postpartum period is the foundation of lifelong well-being, directly influencing a child's development and long-term outcomes, yet most ...
Scientific Research Publishing

Zhang, Y., & Zheng, Y. (2023). Estimating Response Propensities in Nonprobability Surveys Using Machine Learning. Journal of Survey Statistics and Methodology, 11, 123-145.

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...
Scientific Research Publishing

Dinov, I. D. (2023). Model Performance Assessment, Validation, and Improvement. In editor (Ed.), The Springer Series in Applied Machine Learning (Vol. 2853, pp. 477-531 ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...
EurekAlert!

Intelligent XGBoost framework enhances asphalt pavement skid resistance assessment

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...
IEEE

Machine Learning-Based Algorithm for One-Dimensional Wave Spectrum Retrieval from SAR Imagery as Passing Oceanic Eddy

The inversion of the one-dimensional wave spectrum from dual-polarized synthetic aperture radar (SAR) data is performed using machine learning methods, namely Random Forest (RF), eXtreme Gradient ...
Frontiers

Integrating meteorological and breeding data to predict maize yields using machine learning algorithms

Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods have shown ...
The New York Times

Google’s Quantum Computer Makes a Big Technical Leap

Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...