{"id":"https://openalex.org/W2743290385","doi":"https://doi.org/10.1109/tfuzz.2017.2735939","title":"A New Fuzzy Modeling Framework for Integrated Risk Prognosis and Therapy of Bladder Cancer Patients","display_name":"A New Fuzzy Modeling Framework for Integrated Risk Prognosis and Therapy of Bladder Cancer Patients","publication_year":2017,"publication_date":"2017-08-03","ids":{"openalex":"https://openalex.org/W2743290385","doi":"https://doi.org/10.1109/tfuzz.2017.2735939","mag":"2743290385"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2017.2735939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2017.2735939","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"},"type":"article","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/A5046059393","display_name":"Olusayo Obajemu","orcid":"https://orcid.org/0000-0001-6181-9245"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Olusayo Obajemu","raw_affiliation_strings":["Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069916821","display_name":"Mahdi Mahfouf","orcid":"https://orcid.org/0000-0002-7349-5396"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mahdi Mahfouf","raw_affiliation_strings":["Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032231578","display_name":"James W.F. Catto","orcid":"https://orcid.org/0000-0003-2787-8828"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"James W. F. Catto","raw_affiliation_strings":["Department of Oncology and Metabolism, The Medical School, The University of Sheffield, Sheffield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Oncology and Metabolism, The Medical School, The University of Sheffield, Sheffield, U.K","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046059393"],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":null,"apc_paid":null,"fwci":2.0986,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.90261831,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"3","first_page":"1565","last_page":"1577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9994999766349792,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9994999766349792,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8766293525695801},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5775505304336548},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5709526538848877},{"id":"https://openalex.org/keywords/prognostics","display_name":"Prognostics","score":0.542798638343811},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5191999673843384},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.5121467113494873},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5083674788475037},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.4735364615917206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39448317885398865},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.3760015666484833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35178348422050476},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.32414913177490234},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.16147887706756592}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8766293525695801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5775505304336548},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5709526538848877},{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.542798638343811},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5191999673843384},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.5121467113494873},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5083674788475037},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.4735364615917206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39448317885398865},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3760015666484833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35178348422050476},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.32414913177490234},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.16147887706756592},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2017.2735939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2017.2735939","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W311531870","https://openalex.org/W977809029","https://openalex.org/W1543389126","https://openalex.org/W1751358800","https://openalex.org/W1844044367","https://openalex.org/W1983658296","https://openalex.org/W1987084738","https://openalex.org/W2012270441","https://openalex.org/W2016086965","https://openalex.org/W2046575126","https://openalex.org/W2049320546","https://openalex.org/W2050050052","https://openalex.org/W2068052921","https://openalex.org/W2074486916","https://openalex.org/W2082425819","https://openalex.org/W2085826031","https://openalex.org/W2094760805","https://openalex.org/W2129925362","https://openalex.org/W2131256974","https://openalex.org/W2135369095","https://openalex.org/W2146916273","https://openalex.org/W2158698691","https://openalex.org/W2162706466","https://openalex.org/W2171527822","https://openalex.org/W2304576809","https://openalex.org/W2344174278","https://openalex.org/W2465256380","https://openalex.org/W3147894994","https://openalex.org/W4211007335","https://openalex.org/W4245152641","https://openalex.org/W4245266758","https://openalex.org/W4299551643","https://openalex.org/W6625543786","https://openalex.org/W6637628862","https://openalex.org/W6668921528"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W3213192587","https://openalex.org/W2144291498","https://openalex.org/W2535730979","https://openalex.org/W2030958945","https://openalex.org/W2905433371","https://openalex.org/W2370073012","https://openalex.org/W4386567722","https://openalex.org/W2168646784","https://openalex.org/W2466930957"],"abstract_inverted_index":{"This":[0,209],"paper":[1,97],"presents":[2],"a":[3,27,50,136,152,199],"new":[4,28],"fuzzy":[5,37,108,225],"modeling":[6,41,94,109,118,203,261],"approach":[7],"for":[8,30],"analyzing":[9],"censored":[10],"survival":[11,138,201,249],"data":[12,147,202,255],"and":[13,39,84,101,158,161,174,178,227,242,256],"finding":[14],"risk":[15,71,164,170,240,244],"groups":[16,241],"of":[17,34,45,56,60,91,120,183,224,232],"patients":[18,69,83,160],"diagnosed":[19],"with":[20,70,189],"bladder":[21,145],"cancer.":[22],"The":[23,43,124,140,181],"proposed":[24,107,185,260],"framework":[25,48,186,231],"involves":[26],"procedure":[29],"integrating":[31],"the":[32,57,89,96,106,117,121,156,184,190,211,221,228,233,253,259,270,276],"frameworks":[33],"interval":[35],"type-2":[36],"logic":[38],"Cox":[40,192,234],"intrinsically.":[42],"output":[44],"this":[46,77],"synergistic":[47],"is":[49,54,66,126,187,210],"score/prognostics":[51],"index":[52],"which":[53,130,149,275],"indicative":[55],"patient's":[58],"level":[59],"mortality":[61],"risk.":[62],"A":[63],"threshold":[64,78],"value":[65],"selected":[67],"whereby":[68],"scores":[72],"that":[73,99,154],"are":[74,79,103,113],"greater":[75],"than":[76,269],"classed":[80],"as":[81,134,196,198],"high-risk":[82,159],"vice":[85],"versa.":[86],"Unlike":[87],"in":[88,135,236],"case":[90],"black-box":[92],"type":[93],"approaches,":[95],"shows":[98,265],"interpretability":[100],"transparency":[102,222],"maintained":[104],"using":[105],"framework.":[110],"Two":[111],"datasets":[112],"used":[114],"to":[115,143,219,238],"test":[116],"accuracy":[119],"elicited":[122],"models.":[123],"first":[125,212],"an":[127,214],"artificial":[128,254],"dataset":[129],"has":[131,216],"similar":[132],"characteristics":[133],"typical":[137],"data.":[139],"second":[141],"relates":[142],"real-life":[144],"cancer":[146],"from":[148,247],"one":[150],"requires":[151],"model":[153,235],"identifies":[155],"low-risk":[157],"then":[162],"recommends":[163],"management":[165,245],"decisions":[166,246],"based":[167,205],"on,":[168],"predicted":[169],"level,":[171],"patient":[172],"history":[173],"characteristics,":[175],"disease":[176],"pathology,":[177],"event":[179],"times.":[180],"performance":[182],"compared":[188],"traditional":[191],"model,":[193],"logistic":[194],"regression":[195],"well":[197],"nonlinear":[200],"technique":[204],"on":[206],"neural":[207],"networks.":[208],"time":[213],"attempt":[215],"been":[217],"made":[218],"exploit":[220],"advantages":[223],"models":[226,273],"principled":[229],"statistical":[230],"order":[237],"identify":[239],"recommend":[243],"complex":[248],"datasets.":[250],"In":[251],"both":[252],"real":[257],"data,":[258],"framework,":[262],"although":[263],"minimalistic,":[264],"better":[266],"generalization":[267],"performances":[268],"previously":[271],"reported":[272],"against":[274],"results":[277],"were":[278],"compared.":[279]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
