Results 41 to 50 of about 748,707 (290)
Molecular Oncology, EarlyView.LUNAR is a liver‐specific long noncoding RNA (lncRNA) that is highly expressed in normal liver but becomes epigenetically silenced in hepatocellular carcinoma through promoter hypermethylation. Loss of LUNAR is associated with NOTCH activation, epithelial–mesenchymal transition, and metastasis, whereas restoring LUNAR restrains metastatic progression ...
Se Ha Jang +9 more
wiley +1 more source
Why would we choose AUC? [PDF]
, 2012 AUC is known of having most of the Egyptian elite students, this interview is trying to answer why would students pay that much money for ...
Alphons, Marina Anis
core +1 more source
Discover SustainabilityLife cycle assessment (LCA) is crucial for evaluating the environmental impacts of construction buildings and materials throughout their lifespan. The present study seeks to bridge the gap between assessing the LCA and quantifying their environmental ...
Berlant Arab +4 more
doaj +1 more source
Molecular Oncology, EarlyView.This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic +10 more
wiley +1 more source
Calculation of the total number of radiation decay of Radiolabelled-Octreotate using non-linear mixed effect models [PDF]
ITM Web of ConferencesNon-Linear Mixed Effect (NLME) is a method used in the area under the measured time-activity curve (AUC) calculations. The calculation of an accurate AUC is needed for an accurate determination of the radiation absorbed dose.
Pratiwi Nining +2 more
doaj +1 more source
Partial AUC Estimation and Regression
Biometrics, 2003 Summary. Accurate diagnosis of disease is a critical part of health care. New diagnostic and screening tests must be evaluated based on their abilities to discriminate diseased from nondiseased states. The partial area under the receiver operating characteristic (ROC) curve is a measure of diagnostic test accuracy.
Dodd, Lori E., Pepe, Margaret S.
openaire +4 more sources
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 The Area Under the ROC Curve (AUC) is an important model metric for evaluating binary classifiers, and many algorithms have been proposed to optimize AUC approximately. It raises the question of whether the generally insignificant gains observed by previous studies are due to inherent limitations of the metric or the inadequate quality of optimization.
Baojian Zhou, Steven Skiena
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Molecular Oncology, EarlyView.High‐risk bladder cancer is typically treated with Bacillus Calmette‐Guérin (BCG), but 30–40% of patients relapse. No FDA‐ or CE‐approved biomarkers currently predict or prognosticate BCG failure. We systematically reviewed the literature and identified 72 eligible studies, revealing several promising biomarkers associated with BCG treatment response ...
Rui Ribeiro‐Pereira +7 more
wiley +1 more source
Maximize AUC for Positive-Unlabeled Classification and Incremental Algorithm
Jisuanji kexue yu tansuo, 2020 Positive-unlabeled classification is referred to as PU classification. Since there are only positive samples and unlabeled samples, the traditional classification methods are not effective in PU classification.
MA Yumin, WANG Shitong
doaj +1 more source
Stochastic Proximal AUC Maximization
J. Mach. Learn. Res., 2019 In this paper we consider the problem of maximizing the Area under the ROC curve (AUC) which is a widely used performance metric in imbalanced classification and anomaly detection. Due to the pairwise nonlinearity of the objective function, classical SGD algorithms do not apply to the task of AUC maximization.
Yunwen Lei, Yiming Ying
openaire +5 more sources