Results 241 to 250 of about 416,781 (292)

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

[ROC curve]. [PDF]

Semergen, 2023
The ROC curve is a statistical tool used to evaluate the discriminative capacity of a dichotomous diagnostic test. These are curves in which sensitivity is presented as a function of false positives (complementary to specificity) for different cut-off points.
J A, Martínez Pérez, P S, Pérez Martin   +1 more
core   +5 more sources

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ROC SURFACE: A GENERALIZATION OF ROC CURVE ANALYSIS

Journal of Biopharmaceutical Statistics, 2000
Receiver operating characteristic (ROC) curve analysis is widely used in biomedical research to assess the performance of diagnostic tests. Much of the work has been directed at developing accurate indices to describe ROC curves and appropriate statistics to test differences between them.
Harry Yang
exaly   +3 more sources

Analyzing a Portion of the ROC Curve

Medical Decision Making, 1989
The area under the ROC curve is a common index summarizing the information contained in the curve. When comparing two ROC curves, though, problems arise when interest does not lie in the entire range of false-positive rates (and hence the entire area). Numerical integration is suggested for evaluating the area under a portion of the ROC curve. Variance
exaly   +3 more sources

ROC Curve [PDF]

, 2013
ROC curve.
Alberto Garcia-Zamalloa (319006), Jorge Taboada-Gomez (319007)   +1 more
core   +6 more sources

ROC Curve [PDF]

, 2017
The new cut-off of cytokeratin 19 mRNA copy number obtained by the ROC curve. Youden’s index identifies the optimal value at 2150 copies.
Irene Terrenato (95244), Letizia Perracchio (85364), Francesca Rollo (3740299), Franco Di Filippo (393292), Marcella Mottolese (85368), Laura De Salvo (3740305), Beatrice Casini (393293), Valerio D’Alicandro (3740302), Edoardo Pescarmona (393300), Marcello Maugeri-Saccà (435396), Simona Di Filippo (393299), Simonetta Buglioni (85363)   +11 more
openaire   +2 more sources

On the statistical analysis of ROC curves

Statistics in Medicine, 1989
AbstractWe introduce a new accuracy index for receiver operating characteristic (ROC) curves, namely the partial area under the binormal ROC graph over any specified region of interest. We propose a simple but general procedure, based on a conventional analysis of variance, for comparing accuracy indices derived from two or more different modalities ...
M L, Thompson, W, Zucchini
openaire   +2 more sources

ROC curves and the binormal assumption

The Journal of Neuropsychiatry and Clinical Neurosciences, 1991
Previous articles in this series have described how receiver operating characteristic (ROC) graphs provide comprehensive graphic representations of the diagnostic performance of non-binary tests and have explained how one constructs "trapezoidal" ROC graphs in which discrete cutoff points are plotted and connected with line segments.
E, Somoza, D, Mossman
openaire   +2 more sources