A review of feature selection methods for machine learning-based disease risk prediction
Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …
complex datasets. One of the promising applications of machine learning is in precision …
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Objectives The objective of this study was to compare performance of logistic regression
(LR) with machine learning (ML) for clinical prediction modeling in the literature. Study …
(LR) with machine learning (ML) for clinical prediction modeling in the literature. Study …
Low HDL and high triglycerides predict COVID-19 severity
Lipids are indispensable in the SARS-CoV-2 infection process. The clinical significance of
plasma lipid profile during COVID-19 has not been rigorously evaluated. We aim to …
plasma lipid profile during COVID-19 has not been rigorously evaluated. We aim to …
Random forest vs logistic regression: binary classification for heterogeneous datasets
K Kirasich, T Smith, B Sadler - SMU Data Science Review, 2018 - scholar.smu.edu
Selecting a learning algorithm to implement for a particular application on the basis of
performance still remains an ad-hoc process using fundamental benchmarks such as …
performance still remains an ad-hoc process using fundamental benchmarks such as …
Dropout early warning systems for high school students using machine learning
Students' dropouts are a serious problem for students, society, and policy makers. Predictive
modeling using machine learning has a great potential in develo** early warning systems …
modeling using machine learning has a great potential in develo** early warning systems …
Forest fire probability map** in eastern Serbia: Logistic regression versus random forest method
Forest fire risk has increased globally during the previous decades. The Mediterranean
region is traditionally the most at risk in Europe, but continental countries like Serbia have …
region is traditionally the most at risk in Europe, but continental countries like Serbia have …
Essential guidelines for computational method benchmarking
In computational biology and other sciences, researchers are frequently faced with a choice
between several computational methods for performing data analyses. Benchmarking …
between several computational methods for performing data analyses. Benchmarking …
Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease
Introduction Blood-based biomarkers of pathophysiological brain amyloid β (Aβ)
accumulation, particularly for preclinical target and large-scale interventions, are warranted …
accumulation, particularly for preclinical target and large-scale interventions, are warranted …
A random forest based biomarker discovery and power analysis framework for diagnostics research
Background Biomarker identification is one of the major and important goal of functional
genomics and translational medicine studies. Large scale–omics data are increasingly …
genomics and translational medicine studies. Large scale–omics data are increasingly …
Rapidly assessing earthquake-induced landslide susceptibility on a global scale using random forest
Q He, M Wang, K Liu - Geomorphology, 2021 - Elsevier
Earthquake-induced landslides (EQILs) are an incredibly destructive geological disaster.
Rapid landslide susceptibility assessments are indispensable and critical for risk analysis …
Rapid landslide susceptibility assessments are indispensable and critical for risk analysis …