Multi-omics Prognostic Modeling
Multi-Omics Prognostic Modeling is a computational framework that integrates diverse omics data types to predict clinical outcomes by identifying molecular signatures associated with disease progression or treatment response.
81
Publications
5.6K
Citations
541
Authors
262
Institutions
Publications per year
2017–2026
76
Parents
81
Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer
Kumardeep Chaudhary, Olivier Poirion, Liangqun Lu et al. · Clinical Cancer Research · 2017 · 1.1K citations · Full text
Medicine, Bioinformatics, Oncology +17
Multi-omic machine learning predictor of breast cancer therapy response
Stephen‐John Sammut, Mireia Crispin‐Ortuzar, Suet‐Feung Chin et al. · Nature · 2021 · 642 citations · Full text
Medicine, Cancer Biology, Oncology +17
SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer
Zhi Huang, Xiaohui Zhan, Shunian Xiang et al. · Frontiers in Genetics · 2019 · 260 citations · Full text
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University of Hawaiʻi at Mānoa
Honolulu, United States
5 h-index
15 publications
3.8K citations
Cancer Center of Hawaii
Honolulu, United States
4 h-index
12 publications
5.1K citations
Xiangya Hospital Central South University
Changsha, China
4 h-index
21 publications
510 citations

Sun Yat-sen University
Guangzhou, China
4 h-index
17 publications
1.2K citations

Central South University
Changsha, China
4 h-index
21 publications
510 citations
Yale University
New Haven, United States
3 h-index
5 publications
307 citations
University of Pennsylvania
Philadelphia, United States
3 h-index
4 publications
534 citations
University of Michigan
Ann Arbor, United States
3 h-index
5 publications
712 citations
1–8 of 262
5 publications · 246 citations
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5 publications · 180 citations
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5 publications · 307 citations
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3 publications · 118 citations
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3 publications · 320 citations
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