{"id":"https://openalex.org/W7135246497","doi":"https://doi.org/10.48550/arxiv.2603.11598","title":"Survival Meets Classification: A Novel Framework for Early Risk Prediction Models of Chronic Diseases","display_name":"Survival Meets Classification: A Novel Framework for Early Risk Prediction Models of Chronic Diseases","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135246497","doi":"https://doi.org/10.48550/arxiv.2603.11598"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11598","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11598","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11598","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Khan, Shaheer Ahmad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Shaheer Ahmad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129074325","display_name":"Muhammad Usamah Shahid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shahid, Muhammad Usamah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103408949","display_name":"Muddassar Farooq","orcid":"https://orcid.org/0009-0009-1882-7819"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Farooq, Muddassar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5005000233650208,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5005000233650208,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.2718999981880188,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.061900001019239426,"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/predictive-modelling","display_name":"Predictive modelling","score":0.5702000260353088},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.5095000267028809},{"id":"https://openalex.org/keywords/chronic-disease","display_name":"Chronic disease","score":0.4410000145435333},{"id":"https://openalex.org/keywords/prognostic-model","display_name":"Prognostic model","score":0.439300000667572},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.4284999966621399},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.3986000120639801}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6462000012397766},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5702000260353088},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.5095000267028809},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.4627000093460083},{"id":"https://openalex.org/C2987552334","wikidata":"https://www.wikidata.org/wiki/Q383126","display_name":"Chronic disease","level":2,"score":0.4410000145435333},{"id":"https://openalex.org/C2993277928","wikidata":"https://www.wikidata.org/wiki/Q7248370","display_name":"Prognostic model","level":3,"score":0.439300000667572},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41780000925064087},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39739999175071716},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3490999937057495},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34529998898506165},{"id":"https://openalex.org/C50440223","wikidata":"https://www.wikidata.org/wiki/Q1475848","display_name":"Risk factor","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3075999915599823},{"id":"https://openalex.org/C2986432223","wikidata":"https://www.wikidata.org/wiki/Q5449740","display_name":"Risk model","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11598","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11598","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.11598","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11598","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Chronic":[0],"diseases":[1,63],"are":[2],"long-lasting":[3],"conditions":[4],"that":[5,116,136],"require":[6],"lifelong":[7],"medical":[8],"attention.":[9],"Using":[10],"big":[11,112],"EMR":[12,113],"data,":[13],"we":[14,39,76],"have":[15,158],"developed":[16],"early":[17],"disease":[18,45,101],"risk":[19,46,60,102],"prediction":[20],"models":[21,47,56,121,140,149],"for":[22,44,57,99],"five":[23],"common":[24],"chronic":[25,32,62],"diseases:":[26],"diabetes,":[27],"hypertension,":[28],"CKD,":[29],"COPD,":[30],"and":[31,91,128,143],"ischemic":[33],"heart":[34],"disease.":[35],"In":[36,73],"this":[37,74],"study,":[38],"present":[40],"a":[41,96,151,163],"novel":[42,152],"approach":[43],"by":[48,162],"integrating":[49],"survival":[50,68,78,120,148],"analysis":[51,69,79],"with":[52],"classification":[53,71,89],"techniques.":[54],"Traditional":[55],"predicting":[58],"the":[59,117,146],"of":[61,107,119,124,137,165],"predominantly":[64],"focus":[65],"on":[66,110],"either":[67],"or":[70,133],"independently.":[72],"paper,":[75],"show":[77,115],"methods":[80],"can":[81],"be":[82],"re-engineered":[83],"to":[84,87,132,154],"enable":[85],"them":[86,95],"do":[88],"efficiently":[90],"effectively,":[92],"thereby":[93],"making":[94],"comprehensive":[97],"tool":[98],"developing":[100],"surveillance":[103],"models.":[104],"The":[105],"results":[106],"our":[108],"experiments":[109],"real-world":[111],"data":[114],"performance":[118],"in":[122],"terms":[123],"accuracy,":[125],"F1":[126],"score,":[127],"AUROC":[129],"is":[130],"comparable":[131],"better":[134],"than":[135],"prior":[138],"state-of-the-art":[139],"like":[141],"LightGBM":[142],"XGBoost.":[144],"Lastly,":[145],"proposed":[147],"use":[150],"methodology":[153],"generate":[155],"explanations,":[156],"which":[157],"been":[159],"clinically":[160],"validated":[161],"panel":[164],"three":[166],"expert":[167],"physicians.":[168]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-14T00:00:00"}
