Systematic reviews (SRs) provide valuable evidence for guiding new research directions.
However, the manual effort involved in selecting articles for inclusion in an SR is error-prone …

Artificial intelligence (AI) models can play a more effective role in managing patients with the
explosion of digital health records available in the healthcare industry. Machine‐learning …

Even if assessing binary classifications is a common task in scientific research, no
consensus on a single statistic summarizing the confusion matrix has been reached so far …

Purpose To externally test four chest radiograph classifiers on a large, diverse, real-world
dataset with robust subgroup analysis. Materials and Methods In this retrospective study …

The gut microbiome, linked significantly to host diseases, offers potential for disease
diagnosis through machine learning (ML) pipelines. These pipelines, crucial in modeling …

Abstract The Integrated Data Infrastructure (IDI) in New Zealand is a critical asset that
integrates citizen data from various public and private organizations for population-level …

This work integrates logical and physical security processes, and simplifies the
manageability of the security infrastructure. The process increases visibility to resources …

Abstract Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide.
Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the …

This study investigates the effectiveness of six prominent machine learning models—
random forest, decision trees, K-nearest neighbor, logistic regression, support vector …

By organizing knowledge within a research field, Systematic Reviews (SR) provide valuable
leads to steer research. Evidence suggests that SRs have become first-class artifacts in …