Using machine learning to shed light on how well the triage systems work
A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups...
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Reducing inequalities using an unbiased machine learning approach to identify births with the highest risk of preventable neonatal deaths | Population Health Metrics
ApproachIn this research, the unit of analysis is the individual birth. We aim to identify the births with the highest...
Machine learning-driven development of a behaviour-based student classification system (SCS-B) for enhanced educational analytics
This section outlines the operational process of the proposed Student Classification System (SCS-B), which utilizes machine learning techniques. The system...
Prediction of stillbirth using machine learning methods
Data sourceData were extracted from a perinatal database for women who delivered between January 2009 and December 2020 at seven...
A comparative study of machine learning methods for predicting mode I and II brittle fracture in notched bend specimens
Data set visualisationTable 2 presents the characteristics of the dataset used in this study. The input variables across the datasets demonstrate...
A hybrid machine learning-enhanced MCDM model for transport safety engineering
Dynamic evolution of SPIsTo analyze the evolution of specific SPIs over time, we created radar plots, as depicted in Fig. 8....
