Results 91 to 100 of about 488,717 (225)

Value of triglyceride glucose-body mass index in predicting nonalcoholic fatty liver disease in individuals with type 2 diabetes mellitus

Frontiers in Endocrinology
BackgroundThere is limited data on the association between TyG-BMI and NAFLD in patients with Type 2 Diabetes Mellitus (T2DM). The magnitude of risk prediction and predictive efficacy of TyG-BMI for T2DM with NAFLD remains unclear.ObjectiveTo examine the
Xiaoyi Qian, Wenwen Wu, Boyang Chen, Simin Zhang, Chunmei Xiao, Long Chen, Jun Chen, Jun Chen, Lingli Ke, Meian He, Xiulou Li, Xiulou Li, Xiulou Li   +12 more
doaj   +1 more source

Receiver operating characteristic (ROC) curve for fecal calprotectin.

, 2016
Receiver operating characteristic (ROC) curve for fecal calprotectin in prediction the presence of acute appendicitis. The area under the curve (AUC) was 0.869 (95% confidence interval (CI) CI 0.715–1.0), p = 0.009.
Hubert Zirngibl (3608042), Valerie Orth (280906), Daniel Gödde (3608039), Peter C. Ambe (3608045)   +3 more
core   +1 more source

Beyond the ROC Curve: Activity Monitoring to Evaluate Deep Learning Models in Clinical Settings

Applied Medical Informatics
We evaluated ‘VITALCARE-SEPS’, a deep learning model for sepsis prediction, using the activity monitoring operator characteristics curve with two different scoring algorithms.
Hyunwoo CHOO, Kyung Hyun LEE, Sungsoo HONG, Sungjun HONG, Ki-Byung LEE, Chang Youl LEE   +5 more
doaj  

Receiver operating characteristic (ROC) curve for whole cohort.

, 2014
Discriminatory ability for death at one, two, and three years, evaluated by receiver operating characteristic (ROC) curve area, for Okuda, CLIP, BCLC and JIS scores for whole cohort.
Mohamed Saad Hashim (531752), Imam Waked (531753), Asmaa Ibrahim Gomaa (531751)   +2 more
core   +1 more source

ROC (receiver operating characteristic) analysis.

, 2015
1 = ocular residual astigmatism; 2 = Area under the curve; 3 = Spherical Equivalent; 4 = P value
Gisbert Richard (71493), Andreas Frings (703734), Vasyl Druchkiv (723867), Toam Katz (723868), Johannes Steinberg (723866), Stephan J. Linke (703733), Christos Skevas (673410)   +6 more
core   +1 more source

Estimating the Area under a Receiver Operating Characteristic Curve For Repeated Measures Design

The receiver operating characteristic (ROC) curve is widely used for diagnosing as well as for judging the discrimination ability of different statistical models.
Honghu Liu, Tongtong Wu
core  

Receiver operating characteristic (ROC) curve for WBC and CRP.

, 2016
Receiver operating characteristic (ROC) curve for WBC (AUC: 0.728, 95% CI: 0.473–0.983, p = 0.098) and CRP in prediction the presence of acute appendicitis (AUC: 0.316, 95% CI: 0.033–0.593, p = 0.181).
Hubert Zirngibl (3608042), Valerie Orth (280906), Daniel Gödde (3608039), Peter C. Ambe (3608045)   +3 more
core   +1 more source

Validation procedures in radiological diagnostic models. Neural network and logistic regression [PDF]

The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods.
Pedro Delicado, Luis Martí, Estanislao Arana   +2 more
core  

Commentary: A novel and effective ECG method to differentiate right from left ventricular outflow tract arrhythmias: angle-corrected V2S

Frontiers in Cardiovascular Medicine, 2023
Zhuoqiao He, Zhuoqiao He, Ming Liu, Xuerui Tan   +3 more
doaj   +1 more source

KIPPPI Receiver Operating Characteristic (ROC) curve.

, 2013
Receiver Operating Characteristic curve for KIPPPI scales Wellbeing, Competence, Autonomy and KIPPPI Total score, relative to CBCL1.5-5 Total Problem score in the clinical range. AUC = area under the curve.
Carolien L. de Haan (297612), Ingrid Kruizinga (297611), Wilma Jansen (163315), Hein Raat (148332)   +3 more
core   +1 more source