PLoS One
J. Path Informatics
Int J Lab Hematology
Nature's Scientific Reports
Archives of Pathology & Laboratory Medicine
Several groups have previously developed logistic regression models for predicting delayed graft function (DGF). In this study, we used an automated machine learning (ML) modeling pipeline to generate and optimize DGF prediction models en masse.
Transplantation
We conducted a retrospective analysis of 211 adult patients (age ≥ 18 years) with severe burn injury (≥ 20% total body surface area) to generate training and test datasets for ML applications. The MILO-ML approach was compared against an exhaustive “non-automated” ML approach as well as standard statistical methods.
Nature’s Scientific Reports
The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using the novel biomarker, neutrophil gelatinase associated lipocalin (NGAL), combined with contemporary biomarkers such as N-terminal pro B-type natriuretic peptide (NT-proBNP), urine output (UOP), and plasma creatinine.
Nature’s Scientific Reports
This review provides definitions and basic knowledge of machine learning categories, introduces the underlying concept of the bias-variance trade-off as an important foundation in supervised machine learning, and discusses approaches to the supervised machine learning study design along with an overview and description of common supervised machine learning algorithms.
Academic Pathology