Results 31 to 40 of about 474,933 (300)

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 efficiency, but are susceptible to class ratio changes over time. In case of static data, the area under
Dariusz Brzezinski, Jerzy Stefanowski
openaire   +1 more source

The estimated optimism-corrected area under the receiver operating characteristic curve (OC-AUC-ROC), for predictive models developed by different machine learning algorithms and feature selection methods.

, 2022
The estimated optimism-corrected area under the receiver operating characteristic curve (OC-AUC-ROC), for predictive models developed by different machine learning algorithms and feature selection methods.
Reza Yaesoubi (207900), Shiying You (12981374), Melanie H. Chitwood (10092869), Kenneth S. Gunasekera (9330249), Jennifer Furin (435179), Valeriu Crudu (704924), Alexandru Codreanu (12119854), Nelly Ciobanu (8263323), Ted Cohen (118302), Joshua L. Warren (3797263)   +9 more
core   +1 more source

A comparative study of diagnostic accuracy in 3026 pleural biopsies and matched pleural effusion cytology with clinical correlation: A methodological issue

Cancer Medicine, 2023
Aim After reading the article by Ivan K. Poon et al. Certain issues regarding the methodology must be addressed. Result First, it was not sufficient using only sensitivity and specificity. Second, we think the receiver operator characteristic curve (ROC)
Wen‐Li Zhang, Xiang Fang, Jian‐Qing Qiu, Tao Cui   +3 more
doaj   +1 more source

Area under the curve (AUC) analysis for the two experiments.

, 2020
Area under the curve (AUC) analysis for the two experiments.
Huachen Gao (8562048), Xianyu Yu (8562045)   +1 more
core   +1 more source

A relationship between the incremental values of area under the ROC curve and of area under the precision-recall curve

Diagnostic and Prognostic Research, 2021
Background Incremental value (IncV) evaluates the performance change between an existing risk model and a new model. Different IncV metrics do not always agree with each other. For example, compared with a prescribed-dose model, an ovarian-dose model for
Qian M. Zhou, Lu Zhe, Russell J. Brooke, Melissa M. Hudson, Yan Yuan   +4 more
doaj   +1 more source

Estimation of AUC from 0 to Infinity in Serial Sacrifice Designs. [PDF]

, 2005
Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration time curve (AUC).
Wolfsegger, Martin J., Jaki, Thomas
core  

Area under Curve (AUC) comparison.

, 2013
Area under Curve (AUC) comparison measuring the ability of recovering the original PPI networks: (a) Y_Tong, (b) H_Bind, (c) H_InAct, (d) F_BioGrid, (e) H_BioGrid using embedding space dimensions of 1 to 20.
Lin Zhu (192179), De-Shuang Huang (396909), Zhu-Hong You (396908), Bing Wang (126120)   +3 more
core   +1 more source

The human gut microbiome across the life course

FEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Prediction performance (area under curve, AUC) of integrative models.

, 2016
Prediction performance (area under curve, AUC) of integrative models.
Matthew C. Cowperthwaite (93322), Max Shpak (447194), Mark G. Burnett (2636200), Jie Lu (139953)   +3 more
core   +1 more source