{"id":"https://openalex.org/W2962360156","doi":"https://doi.org/10.1109/isbi.2019.8759301","title":"Deep Convolutional Neural Networks For Imaging Data Based Survival Analysis Of Rectal Cancer","display_name":"Deep Convolutional Neural Networks For Imaging Data Based Survival Analysis Of Rectal Cancer","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2962360156","doi":"https://doi.org/10.1109/isbi.2019.8759301","mag":"2962360156","pmid":"https://pubmed.ncbi.nlm.nih.gov/31929858"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2019.8759301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5100369954","display_name":"Hongming Li","orcid":"https://orcid.org/0000-0001-6934-1928"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongming Li","raw_affiliation_strings":["Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Departments of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Departments of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077037935","display_name":"Pamela Boimel","orcid":"https://orcid.org/0000-0002-9771-1700"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pamela Boimel","raw_affiliation_strings":["Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014079341","display_name":"James Janopaul\u2010Naylor","orcid":"https://orcid.org/0000-0002-3612-4852"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Janopaul-Naylor","raw_affiliation_strings":["Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101814321","display_name":"Haoyu Zhong","orcid":"https://orcid.org/0009-0000-0176-0704"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoyu Zhong","raw_affiliation_strings":["Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079985074","display_name":"Ying Xiao","orcid":"https://orcid.org/0000-0001-8558-6394"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Xiao","raw_affiliation_strings":["Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061377078","display_name":"Edgar Ben\u2010Josef","orcid":"https://orcid.org/0000-0003-1292-9565"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edgar Ben-Josef","raw_affiliation_strings":["Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102908819","display_name":"Yong Fan","orcid":"https://orcid.org/0000-0001-9977-6113"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Fan","raw_affiliation_strings":["Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","Departments of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Departments of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":11.0149,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.98788338,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"2019","issue":null,"first_page":"846","last_page":"849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10335","display_name":"Colorectal Cancer Surgical Treatments","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7470894455909729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7469632625579834},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7287893891334534},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7125279903411865},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6880006194114685},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.5531986355781555},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5174673199653625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48065221309661865},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4308319687843323},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.41982680559158325},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10044750571250916},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06760722398757935}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7470894455909729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7469632625579834},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7287893891334534},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125279903411865},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6880006194114685},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.5531986355781555},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5174673199653625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48065221309661865},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4308319687843323},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.41982680559158325},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10044750571250916},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06760722398757935}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isbi.2019.8759301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","raw_type":"proceedings-article"},{"id":"pmid:31929858","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31929858","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:europepmc.org:6061119","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6955095","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G247489268","display_name":null,"funder_award_id":"R21 CA223358","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G3415959687","display_name":null,"funder_award_id":"R01EB022573","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G6258998","display_name":"Biomedical Image Computing and Informatics Cluster","funder_award_id":"1s10od023495-01","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320324099","display_name":"Russian Science Foundation","ror":"https://ror.org/03y2gwe85"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1580788756","https://openalex.org/W2052825782","https://openalex.org/W2074703669","https://openalex.org/W2099698084","https://openalex.org/W2109255472","https://openalex.org/W2128739912","https://openalex.org/W2144717403","https://openalex.org/W2174661749","https://openalex.org/W2347111694","https://openalex.org/W2350997045","https://openalex.org/W2415877456","https://openalex.org/W2428512457","https://openalex.org/W2496251701","https://openalex.org/W2525157777","https://openalex.org/W2525205678","https://openalex.org/W2557738935","https://openalex.org/W2571620227","https://openalex.org/W2963264509","https://openalex.org/W3099478002","https://openalex.org/W3147894994","https://openalex.org/W6716448252","https://openalex.org/W6723340777"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W2810679507","https://openalex.org/W4372048956","https://openalex.org/W4206989953","https://openalex.org/W4323287533","https://openalex.org/W4360994352"],"abstract_inverted_index":{"Recent":[0],"radiomic":[1,13,25,138],"studies":[2,26,41],"have":[3,46],"witnessed":[4],"promising":[5],"performance":[6,56],"of":[7,33,120],"deep":[8,22,65,78],"learning":[9,12,23,66],"techniques":[10,54],"in":[11,30,83],"features":[14,76,139],"and":[15,116,145],"fusing":[16],"multimodal":[17],"imaging":[18,60,75,114],"data.":[19],"Most":[20],"existing":[21,51],"based":[24,110],"build":[27,69],"predictive":[28],"models":[29,72,134],"a":[31,64,84,98,112,117],"setting":[32],"pattern":[34],"classification,":[35],"not":[36],"appropriate":[37],"for":[38,125],"survival":[39,52,70,132,147],"analysis":[40,53],"where":[42],"some":[43],"data":[44],"samples":[45],"incomplete":[47],"observations.":[48],"To":[49,88],"improve":[50],"whose":[55],"is":[57,103],"hinged":[58],"on":[59,111],"features,":[61],"we":[62],"propose":[63],"method":[67,106,150],"to":[68,93],"regression":[71],"by":[73],"optimizing":[74],"with":[77,95,131],"convolutional":[79],"neural":[80],"networks":[81],"(CNNs)":[82],"proportional":[85,142],"hazards":[86,143],"model.":[87],"make":[89],"the":[90],"CNNs":[91],"applicable":[92],"tumors":[94],"varied":[96],"sizes,":[97],"spatial":[99],"pyramid":[100],"pooling":[101],"strategy":[102],"adopted.":[104],"Our":[105],"has":[107],"been":[108],"validated":[109],"simulated":[113],"dataset":[115,119],"FDG-PET/CT":[118],"rectal":[121,128],"cancer":[122],"patients":[123],"treated":[124],"locally":[126],"advanced":[127],"cancer.":[129],"Compared":[130],"prediction":[133,153],"built":[135],"upon":[136],"hand-crafted":[137],"using":[140],"Cox":[141],"model":[144],"random":[146],"forests,":[148],"our":[149],"achieved":[151],"competitive":[152],"performance.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":3}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}