EurekAlert!

AI-accelerated gas sensing: a first-principles–guided machine learning platform for black phosphorus sensors

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Morning Overview on MSN

Scientists build a ‘periodic table’ for AI models

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
Visual Studio Magazine

Decision Tree Regression from Scratch with Pointers 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 ...
Frontiers

Prediction of compressive strength of high-performance concrete based on multiple machine learning models

1 Architectural and Civil Engineering, Jinken College of Technology, Nanjing, Jiangsu, China 2 College of Civil Engineering and Architecture, Xinjiang University, Urumqi, Xinjiang, China Therefore, ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
IEEE

Using Permutation-Based Feature Importance for Improved Machine Learning Model Performance at Reduced Costs

Abstract: In Software Quality Assurance (SQA), predicting defect-prone software modules is essential for ensuring software reliability and consistency. This task is commonly achieved through Machine ...