{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-neural-networks-for-survival-analysis","title":"Deep Neural Networks for Survival Analysis Based on a Multi-Task Framework","arxiv_id":"1801.05512","date":"2018-01-17","proceeding":null,"authors":["Stephane Fotso"],"abstract":"Survival analysis/time-to-event models are extremely useful as they can help\ncompanies predict when a customer will buy a product, churn or default on a\nloan, and therefore help them improve their ROI. In this paper, we introduce a\nnew method to calculate survival functions using the Multi-Task Logistic\nRegression (MTLR) model as its base and a deep learning architecture as its\ncore. Based on the Concordance index (C-index) and Brier score, this method\noutperforms the MTLR in all the experiments disclosed in this paper as well as\nthe Cox Proportional Hazard (CoxPH) model when nonlinear dependencies are\nfound.","url_abs":"http://arxiv.org/abs/1801.05512v1","url_pdf":"http://arxiv.org/pdf/1801.05512v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-neural-networks-for-survival-analysis","repo_url":"https://github.com/havakv/pycox","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"deep-neural-networks-for-survival-analysis","repo_url":"https://github.com/mkazmier/torchmtlr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"survival-analysis","task_name":"Survival Analysis"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1801.05512","atlas_url":"https://app.syntology.ai/?focus=1801.05512","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}