Results 41 to 50 of about 2,344,066 (336)

Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve [PDF]

Neural Computation, 2016
The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking to biometric screening to medicine, performance is measured not in terms of the full area ...
H. Narasimhan, S. Agarwal
semanticscholar   +1 more source

Beyond the ROC Curve: The IMCP Curve

Analytics
The ROC curve [...]
Jesus S. Aguilar-Ruiz
doaj   +1 more source

Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps?

, 2018
This study investigates how effective the receiver operating characteristic (ROC) curve is for comparing the reliability of landslide susceptibility maps (LSMs).
V. Vakhshoori, M. Zare
semanticscholar   +1 more source

Diagnostic Accuracy of Anthropometric Indicators in the Prediction of Urinary Incontinence in Physically Active Older Women [PDF]

Revista Brasileira de Ginecologia e Obstetrícia, 2016
Purpose To determine the diagnostic accuracy and the cutoff point of the variables conicity index, waist to height ratio and fat percentage to detect urinary incontinence in physically active older women. Method A total of 152 women were analyzed. The
Enaiane Cristina Menezes, Janeisa Franck Virtuoso, Eduardo Capeletto, Lislayne Luiza da Silva, Jodelle Machado Chagas, Giovana Zarpellon Mazo   +5 more
doaj   +1 more source

easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment

The R Journal, 2016
ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls.
Dincer Goksuluk, Selçuk Korkmaz, G. Zararsiz, A. E. Karaagaoglu   +3 more
semanticscholar   +1 more source

Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning‐Based Approaches

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser, Alice Bizeul, Meera Chitlur, Hugo Donato, Jelena Roganovic, Julia E. Vogt, Thomas Kühne   +6 more
wiley   +1 more source

In vitro properties of patient serum predict clinical outcome after high dose rate brachytherapy of hepatocellular carcinoma

Molecular Oncology, EarlyView.
Following high dose rate brachytherapy (HDR‐BT) for hepatocellular carcinoma (HCC), patients were classified as responders and nonresponders. Post‐therapy serum induced increased BrdU incorporation and Cyclin E expression of Huh7 and HepG2 cells in nonresponders, but decreased levels in responders.
Lukas Salvermoser, Jan Niklas Schäfer, Shraga Nahum Goldberg, Philipp Maximilian Kazmierczak, Moritz Nikolaus Gröper, Philipp Franz Linden, Elif Öcal, Tanja Burkard, Stefanie Corradini, Najib Ben Khaled, Moritz Wildgruber, Max Seidensticker, Jens Ricke, Matthias Stechele, Marianna Alunni‐Fabbroni   +14 more
wiley   +1 more source

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies

BMC Medical Informatics and Decision Making, 2011
Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated ...
Zumbrunn Thomas, Rousson Valentin
doaj   +1 more source

Prequential AUC: properties of the area under the ROC curve for data streams with concept drift

Knowledge and Information Systems, 2017
Modern data-driven systems often require classifiers capable of dealing with streaming imbalanced data and concept changes. The assessment of learning algorithms in such scenarios is still a challenge, as existing online evaluation measures focus on ...
D. Brzezinski, J. Stefanowski
semanticscholar   +1 more source

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

Molecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker, Keren Zohar, Martin Böttcher, Thomas Wartmann, Henry Freudenstein, Maximilian Doelling, Mihailo Andric, Wenjie Shi, Or Kakhlon, Katrin Hippe, Beatrix Jahnke, Dimitrios Mougiakakos, Franziska Baenke, Daniel Stange, Roland S. Croner, Michal Linial, Ulf D. Kahlert   +16 more
wiley   +1 more source