Results 171 to 180 of about 430,234 (233)

Comparison of GNNs against benchmarks on complete blood count data for sepsis classification (higher values represent better performance) and their required training time. We evaluated the classification performance on two datasets (internal and external dataset). Bold values represent the best values in each column. MCC (Matthew’s Correlation Coefficient), AUROC (Area under receiver operating curve).

Daniel Walke (21680915), Daniel Steinbach (78339), Sebastian Gibb (5842832), Thorsten Kaiser (427544), Gunter Saake (7255616), Paul C. Ahrens (21680918), David Broneske (21680921), Robert Heyer (1643680)   +7 more
openalex   +1 more source

Integrated Prediction System for Individualized Ovarian Stimulation and Ovarian Hyperstimulation Syndrome Prevention: Algorithm Development and Validation.

J Med Internet Res
Chen J, Zhao J, Qiu H, Liu Y, Zhang Y, Sun Q, Yi Y, Tang H, Zhao J, Xu B, Zhang Q, Yang G, Li H, Liu J, Yang Z, Liang S, Li Y, Fu J.   +17 more
europepmc   +1 more source

Development and External Validation of a Machine Learning Model for Predicting Wound Infection in Diabetic Foot Ulcers. [PDF]

Diabetes Metab Syndr Obes
Nie X, Jiang Y, Meng X, Liu J, Zhao H, Chen Y, Wang J, Lu T.   +7 more
europepmc   +1 more source

An interpretable machine-learning model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury. [PDF]

Front Med (Lausanne)
Wang JZ, Zhang N, Ma RR, Yang M, Chen YG, Zhou WJ.   +5 more
europepmc   +1 more source

Development and validation of simplified prognostic models for 14- and 30-day mortality in advanced cancer: beyond the glasgow prognostic score. [PDF]

Front Oncol
Huang JL, Yang WL.
europepmc   +1 more source

External validation of a prognostic model predicting renal graft function one year after brain-dead donor kidney transplantation. [PDF]

Langenbecks Arch Surg
Tessmer P, Weigle CA, Meister FA, Wiemann BA, Gwinner W, Mühlfeld A, Kramann R, Kleine-Döpke D, Richter N, Oldhafer F, Vondran FWR, Schrem H, Beetz O, Zwirner U.   +13 more
europepmc   +1 more source

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

J Med Internet Res
Yoo HY, Shin H, Kim EJ, Son YJ.
europepmc   +1 more source

Hypoxemia prediction in pediatric patients under general anesthesia using machine learning: A retrospective observational study and external validation. [PDF]

PLoS One
Baek S, Park JB, Heo J, Kim K, Baek D, Oh C, Lee HC, Lee D, Hong B.   +8 more
europepmc   +1 more source