{"id":"https://openalex.org/W2933350179","doi":"https://doi.org/10.1007/978-3-030-16145-3_9","title":"CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis","display_name":"CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2933350179","doi":"https://doi.org/10.1007/978-3-030-16145-3_9","mag":"2933350179"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-16145-3_9","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-16145-3_9","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112488340","display_name":"Garima Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Garima Gupta","raw_affiliation_strings":["TCS Research Lab, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"TCS Research Lab, New Delhi, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113145191","display_name":"Vishal Sunder","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vishal Sunder","raw_affiliation_strings":["TCS Research Lab, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"TCS Research Lab, New Delhi, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064173467","display_name":"Ranjitha Prasad","orcid":"https://orcid.org/0000-0002-2649-7882"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ranjitha Prasad","raw_affiliation_strings":["TCS Research Lab, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"TCS Research Lab, New Delhi, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038397893","display_name":"Gautam Shroff","orcid":"https://orcid.org/0000-0002-0340-0283"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gautam Shroff","raw_affiliation_strings":["TCS Research Lab, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"TCS Research Lab, New Delhi, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112488340"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":10.7977,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.98389761,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"108","last_page":"122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9728000164031982,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7742555141448975},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6074605584144592},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5781078934669495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5618795156478882},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.5450388193130493},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.5319880247116089},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.5194608569145203},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47892531752586365},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.46714138984680176},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4505607485771179},{"id":"https://openalex.org/keywords/hazard","display_name":"Hazard","score":0.4444286823272705},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3595334589481354},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2930426001548767},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2265506088733673},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1020486056804657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742555141448975},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6074605584144592},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5781078934669495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5618795156478882},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.5450388193130493},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.5319880247116089},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.5194608569145203},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47892531752586365},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.46714138984680176},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4505607485771179},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.4444286823272705},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3595334589481354},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2930426001548767},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2265506088733673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1020486056804657},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-030-16145-3_9","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-16145-3_9","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1866990630","https://openalex.org/W1979300931","https://openalex.org/W1986705681","https://openalex.org/W1998284002","https://openalex.org/W2038981426","https://openalex.org/W2049045003","https://openalex.org/W2052825782","https://openalex.org/W2061918355","https://openalex.org/W2064675550","https://openalex.org/W2073023604","https://openalex.org/W2073140442","https://openalex.org/W2088229392","https://openalex.org/W2092648747","https://openalex.org/W2108673310","https://openalex.org/W2136883754","https://openalex.org/W2169975204","https://openalex.org/W2294550615","https://openalex.org/W2396881363","https://openalex.org/W2518108298","https://openalex.org/W2571620227","https://openalex.org/W2605397892","https://openalex.org/W2753919178","https://openalex.org/W2789172526","https://openalex.org/W3099478002","https://openalex.org/W3138496105","https://openalex.org/W4244009405","https://openalex.org/W4253599671","https://openalex.org/W4293241248","https://openalex.org/W6600031136","https://openalex.org/W6630875914"],"related_works":["https://openalex.org/W2109650667","https://openalex.org/W2083447308","https://openalex.org/W2064181951","https://openalex.org/W3015225818","https://openalex.org/W4308165859","https://openalex.org/W3127763960","https://openalex.org/W2147995538","https://openalex.org/W2155829550","https://openalex.org/W2163947145","https://openalex.org/W4211065811"],"abstract_inverted_index":null,"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}