{"id":"https://openalex.org/W7163048372","doi":"https://doi.org/10.48550/arxiv.2605.31014","title":"SDM-Q: Cost-Aware Staged Decision-Making for Multi-Omics Classification with Deep Q-Learning","display_name":"SDM-Q: Cost-Aware Staged Decision-Making for Multi-Omics Classification with Deep Q-Learning","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163048372","doi":"https://doi.org/10.48550/arxiv.2605.31014"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.31014","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31014","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2605.31014","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137612061","display_name":"Nan Mu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mu, Nan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xiao, Yangfan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Yangfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Ling","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Li, Xiaoning","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaoning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kang, Yue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhao, Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Chen","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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.3131999969482422,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.3131999969482422,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11642","display_name":"Genomics and Rare Diseases","score":0.0778999999165535,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.07209999859333038,"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/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7024999856948853},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5771999955177307},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5615000128746033},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5310999751091003},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5066999793052673},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.484499990940094}],"concepts":[{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7024999856948853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851000189781189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6179999709129333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6146000027656555},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5771999955177307},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5615000128746033},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5066999793052673},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29179999232292175},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.31014","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31014","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.31014","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31014","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5781553387641907,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-omics":[0],"data":[1],"provide":[2],"complementary":[3],"molecular":[4],"characterizations":[5],"of":[6,199,215,240],"disease":[7,15],"phenotypes":[8],"and":[9,17,30,48,67,110,119,131,137,153,166,191,197,223],"play":[10],"an":[11,102,233],"important":[12],"role":[13],"in":[14,20,45,51],"diagnosis":[16,73],"subtype":[18],"classification":[19,135,179,204],"precision":[21,241],"medicine.":[22],"However,":[23],"acquiring":[24],"complete":[25,185],"multi-omics":[26,69,72,160,186],"profiles":[27],"is":[28,74,124,147],"expensive":[29],"time-consuming,":[31],"while":[32,176,211],"most":[33],"existing":[34],"deep":[35],"learning":[36,63],"methods":[37,183],"assume":[38],"full":[39],"modality":[40,104,139,174],"availability":[41],"during":[42],"inference,":[43],"resulting":[44],"substantial":[46],"redundancy":[47],"limited":[49],"practicality":[50],"clinical":[52],"settings.":[53],"To":[54,115],"address":[55],"this":[56],"issue,":[57],"we":[58],"propose":[59],"SDM-Q,":[60],"a":[61,77,207],"reinforcement":[62],"framework":[64],"for":[65,221,236],"adaptive":[66],"cost-aware":[68,229],"classification.":[70],"Specifically,":[71],"reformulated":[75],"as":[76],"finite-horizon":[78],"sequential":[79,230],"decision":[80,108],"problem,":[81],"where":[82],"the":[83,89,107,112,122,128,189,212,238],"currently":[84],"acquired":[85,216],"omics":[86,209],"modalities":[87,217],"define":[88],"diagnostic":[90,117],"state":[91],"at":[92,127],"each":[93],"stage.":[94],"An":[95],"action--value":[96],"function":[97],"determines":[98],"whether":[99],"to":[100,149],"acquire":[101],"additional":[103],"or":[105],"terminate":[106],"process":[109],"output":[111],"final":[113],"prediction.":[114],"balance":[116],"utility":[118],"acquisition":[120,140,175],"cost,":[121],"reward":[123],"defined":[125],"only":[126,206],"terminal":[129],"stage":[130],"jointly":[132],"determined":[133],"by":[134],"correctness":[136],"cumulative":[138],"cost.":[141],"A":[142],"backward":[143],"stage-wise":[144],"optimization":[145],"strategy":[146],"introduced":[148],"improve":[150],"policy":[151],"consistency":[152],"training":[154],"stability.":[155],"Experiments":[156],"on":[157],"four":[158],"public":[159],"datasets,":[161,193],"including":[162],"ROSMAP,":[163],"LGG,":[164],"BRCA,":[165],"KIPAN,":[167],"demonstrate":[168],"that":[169,228],"SDM-Q":[170],"effectively":[171],"reduces":[172],"redundant":[173],"maintaining":[177],"competitive":[178],"performance":[180],"compared":[181],"with":[182],"using":[184,205],"inputs.":[187],"In":[188],"BRCA":[190],"KIPAN":[192],"more":[194],"than":[195],"99\\%":[196],"95\\%":[198],"subjects,":[200],"respectively,":[201],"achieve":[202],"accurate":[203],"single":[208],"modality,":[210],"average":[213],"number":[214],"remains":[218],"below":[219],"two":[220],"ROSMAP":[222],"LGG.":[224],"These":[225],"results":[226],"suggest":[227],"decision-making":[231],"provides":[232],"effective":[234],"paradigm":[235],"improving":[237],"efficiency":[239],"medicine":[242],"workflows.":[243]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-02T00:00:00"}