Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Abstract: Accurate battery lifetime estimation is crucial for health management and system safety. Data-driven research yields extensive feature sets, yet optimal feature selection is often impeded by ...

What if vaccine development didn’t have to take a decade? This piece looks at how AI is helping scientists ask better ...

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 ...

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 ...

1 Department of Geomatic Engineering, University of Mines and Technology, Tarkwa, Ghana. 2 Department of Geomatic and Civil Engineering, University of Mines and Technology, Essikado, Ghana. Accurate ...

Figure 1: LASSO feature ranking and SHAP explanatory for Cases 1, 2, and 3 feature selection models. A positive SHAP value indicates a positive impact on prediction, leading the model to predict 1 ...

Background: Attention Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental disorder, but its diagnosis remains constrained. This study aimed to identify potential candidate ...

Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...