Results 31 to 40 of about 302,402 (283)

The genetic interpretation of area under the ROC curve in genomic profiling. [PDF]

PLoS Genetics, 2010
Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease.
Naomi R Wray, Jian Yang, Michael E Goddard, Peter M Visscher   +3 more
doaj   +1 more source

Time-dependent ROC curve analysis in medical research: current methods and applications

BMC Medical Research Methodology, 2017
Background ROC (receiver operating characteristic) curve analysis is well established for assessing how well a marker is capable of discriminating between individuals who experience disease onset and individuals who do not.
Adina Najwa Kamarudin, Trevor Cox, Ruwanthi Kolamunnage-Dona   +2 more
doaj   +1 more source

ROCS: receiver operating characteristic surface for class-skewed high-throughput data. [PDF]

PLoS ONE, 2012
The receiver operating characteristic (ROC) curve is an important tool to gauge the performance of classifiers. In certain situations of high-throughput data analysis, the data is heavily class-skewed, i.e.
Tianwei Yu
doaj   +1 more source

On optimal reject rules and ROC curves [PDF]

Pattern Recognition Letters, 2005
In this paper we make the connection between two approaches for supervised classification with a rejection option. The first approach is due to Tortorella and is based on ROC curves and the second is a generalisation of Chow's optimal rule.
Pires, Ana M., Santos-Pereira, Carla
openaire   +4 more sources

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Monitoring Livestock Health by Modeling Rumination Behavior According to Accelerometer-Based Information [PDF]

Journal of Agricultural Machinery
IntroductionThe livestock sector excels in the production of dairy and meat products. These products, serving as vital sources of animal protein, hold a significant position in household diets.
E. Vahedi Tekmehdash, H. Navid, H. Ghasemzadeh, H. Karimi, M. Javani Holan   +4 more
doaj   +1 more source

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 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