netDx: interpretable patient classification using integrated patient similarity networks

Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predi...

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Vydáno v:	Molecular systems biology Ročník 15; číslo 3; s. e8497 - n/a
Hlavní autoři:	Pai, Shraddha, Hui, Shirley, Isserlin, Ruth, Shah, Muhammad A, Kaka, Hussam, Bader, Gary D
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 01.03.2019 EMBO Press John Wiley and Sons Inc Springer Nature
Témata:	Age Algorithms Asthma Asthma - classification Asthma - diagnosis Asthma - genetics Automation Benchmarking Breast cancer Breast Neoplasms - classification Breast Neoplasms - diagnosis Breast Neoplasms - genetics Classification Classifiers EMBO10 EMBO17 EMBO42 Female Gene expression Genomes Genomics Humans Learning Learning algorithms Machine Learning multimodal data integration multi‐omics patient similarity networks Patients Precision medicine Prognosis Queries Recommender systems Similarity Similarity measures Software supervised machine learning Survival Analysis Therapeutic applications Workflow supervised machine learning patient similarity networks precision medicine multimodal data integration multi‐omics
ISSN:	1744-4292, 1744-4292
On-line přístup:	Získat plný text
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