{"id":"https://openalex.org/W4390970046","doi":"https://doi.org/10.1109/bibm58861.2023.10385704","title":"Evaluating SHAP\u2019s Robustness in Precision Medicine: Effect of Filtering and Normalization","display_name":"Evaluating SHAP\u2019s Robustness in Precision Medicine: Effect of Filtering and Normalization","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390970046","doi":"https://doi.org/10.1109/bibm58861.2023.10385704"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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/A5015279499","display_name":"Masrur Sobhan","orcid":"https://orcid.org/0000-0002-1515-4366"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masrur Sobhan","raw_affiliation_strings":["Florida International University,Knight Foundation School of Computing and Information Sciences,Miami,Florida,USA","Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida International University,Knight Foundation School of Computing and Information Sciences,Miami,Florida,USA","institution_ids":["https://openalex.org/I19700959"]},{"raw_affiliation_string":"Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, Florida, USA","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045295085","display_name":"Ananda Mohan Mondal","orcid":"https://orcid.org/0000-0002-4005-9942"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ananda Mohan Mondal","raw_affiliation_strings":["Florida International University,Knight Foundation School of Computing and Information Sciences,Miami,Florida,USA","Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida International University,Knight Foundation School of Computing and Information Sciences,Miami,Florida,USA","institution_ids":["https://openalex.org/I19700959"]},{"raw_affiliation_string":"Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, Florida, USA","institution_ids":["https://openalex.org/I19700959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19700959"],"apc_list":null,"apc_paid":null,"fwci":0.7931,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77676685,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3157","last_page":"3164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.991599977016449,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.991599977016449,"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/T10862","display_name":"AI in cancer detection","score":0.9904000163078308,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7027438282966614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6791583299636841},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6667456030845642},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6465122699737549},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6079859733581543},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4916148781776428}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7027438282966614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6791583299636841},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6667456030845642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6465122699737549},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6079859733581543},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4916148781776428},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1902920598","https://openalex.org/W1967997862","https://openalex.org/W2012771827","https://openalex.org/W2038128936","https://openalex.org/W2072602203","https://openalex.org/W2097117811","https://openalex.org/W2155889930","https://openalex.org/W2172246201","https://openalex.org/W2295598076","https://openalex.org/W2309067861","https://openalex.org/W2521002152","https://openalex.org/W2918618349","https://openalex.org/W2945020349","https://openalex.org/W2962862931","https://openalex.org/W2990029798","https://openalex.org/W3092776451","https://openalex.org/W3133653953","https://openalex.org/W3140415241","https://openalex.org/W3216119570","https://openalex.org/W4213070443","https://openalex.org/W4221079115","https://openalex.org/W4226126697","https://openalex.org/W4306403570","https://openalex.org/W4309322228","https://openalex.org/W4313469582","https://openalex.org/W4313527330","https://openalex.org/W4323905478","https://openalex.org/W4362508795","https://openalex.org/W4367051143","https://openalex.org/W4367299262","https://openalex.org/W4377233234","https://openalex.org/W4382787257","https://openalex.org/W4388677784","https://openalex.org/W6698498768","https://openalex.org/W6737947904","https://openalex.org/W6803880754","https://openalex.org/W6851508571"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Local":[0],"interpretation":[1,48],"of":[2,45,59,75,97,135,190,201,216,226],"explainable":[3],"AI,":[4],"SHAP":[5,104,237,247],"(SHapley":[6],"Additive":[7],"exPlanations),":[8],"in":[9,62,236],"disease":[10],"classification":[11,124],"problems":[12],"offers":[13],"significant":[14],"feature":[15,117],"scores":[16,96,200],"for":[17,79],"each":[18],"sample,":[19],"potentially":[20],"identifying":[21],"precision":[22,80],"medicine":[23,81],"targets.":[24],"Tailoring":[25],"treatments":[26],"based":[27],"on":[28,187],"individual":[29],"genetic":[30],"and":[31,89,150,164,180,230,256],"molecular":[32],"targets":[33],"can":[34],"enhance":[35],"therapeutic":[36],"outcomes":[37],"while":[38],"minimizing":[39],"side":[40],"effects.":[41],"However,":[42],"the":[43,50,73,94,120,133,188,198,224,234],"suitability":[44],"SHAP's":[46],"local":[47,77],"at":[49],"patient":[51],"level":[52],"remains":[53],"uncertain.":[54],"It":[55],"generates":[56],"different":[57,86,112,169,210,214,240],"sets":[58,215],"patient-specific":[60,98,116,217],"genes":[61],"various":[63],"runs,":[64],"even":[65],"with":[66,248],"consistent":[67],"overall":[68],"accuracies.":[69],"This":[70],"uncertainty":[71],"challenges":[72],"reliability":[74],"SHAP\u2019s":[76],"interpretations":[78],"applications.":[82],"Not":[83],"only":[84],"that,":[85],"filtering":[87,229],"criteria":[88],"normalization":[90,176,231],"techniques":[91],"may":[92],"influence":[93],"contribution":[95],"features.":[99,218],"To":[100],"validate":[101],"our":[102,221],"hypothesis,":[103],"was":[105],"applied":[106],"to":[107,114,131,260],"machine":[108,141,159,203,250,262],"learning":[109,142,160,204,251,263],"algorithms":[110,252],"from":[111,119],"genres":[113],"identify":[115],"contributions":[118],"breast":[121],"cancer":[122],"subtype":[123],"problem.":[125],"The":[126],"program":[127],"underwent":[128],"multiple":[129,154],"runs":[130,211],"assess":[132],"robustness":[134],"SHAP.Our":[136],"study":[137,194,243],"demonstrates":[138],"that":[139,174,197,245],"shallow":[140,249],"algorithms,":[143],"like":[144,162],"Logistic":[145],"Regression,":[146],"consistently":[147],"provided":[148],"stable":[149,255],"reliable":[151],"results":[152,238,258],"across":[153,168,209,239],"runs.":[155,170,241],"In":[156,219],"contrast,":[157],"complex":[158,202,261],"models":[161,205],"XGBoost":[163,191],"MLP":[165],"exhibited":[166],"inconsistencies":[167],"Moreover,":[171],"we":[172],"found":[173],"data":[175],"techniques,":[177,232],"particularly":[178],"z-score":[179],"min-max":[181],"normalization,":[182],"had":[183],"a":[184],"minimal":[185],"effect":[186],"performance":[189],"models.":[192],"Our":[193,242],"also":[195],"shows":[196],"accuracy":[199],"remained":[206],"relatively":[207],"constant":[208],"but":[212],"produced":[213],"conclusion,":[220],"findings":[222],"underscore":[223],"importance":[225],"selecting":[227],"appropriate":[228],"given":[233],"variability":[235],"indicates":[244],"combining":[246],"yields":[253],"more":[254],"dependable":[257],"compared":[259],"approaches.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}