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 …

NSAIDs, non-steroidal anti-inflammatory drugs, are one of the most commonly prescribed
pain medications. It is a highly effective drug class for pain and inflammation; however …

Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …

Introduction We aimed to assess whether machine learning models are superior at
predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional …

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality
rate, and it induces other diseases. Since there are no obvious symptoms during the early …

Objectives: To develop an acute kidney injury risk prediction model using electronic health
record data for longitudinal use in hospitalized patients. Design: Observational cohort study …

In data-driven medical research, multi-center studies have long been preferred over single-
center ones due to a single institute sometimes not having enough data to obtain sufficient …

Using artificial intelligence and machine learning techniques in different medical fields,
especially emergency medicine is rapidly growing. In this paper, studies conducted in the …

Background: A major problem in treating acute kidney injury (AKI) is that clinical criteria for
recognition are markers of established kidney damage or impaired function; treatment …

Objective The study sought to describe the prevalence and nature of clinical expert
involvement in the development, evaluation, and implementation of clinical decision support …