Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.
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| Title: | Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment. |
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| Authors: | Benzekry S; Computational Pharmacology and Clinical Oncology (COMPO), Inria Sophia Antipolis-Méditerranée, Cancer Research Center of Marseille, Inserm UMR1068, CNRS UMR7258, Aix Marseille University UM105, Marseille, France., Mastri M; Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, United States of America., Nicolò C; InSilicoTrials Technologies S.P.A, Riva Grumula, Trieste, Italy., Ebos JML; Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, United States of America.; Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, New York, United States of America. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2024 May 03; Vol. 20 (5), pp. e1012088. Date of Electronic Publication: 2024 May 03 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1012088 |
