{"id":"https://openalex.org/W2806086905","doi":"https://doi.org/10.1109/isbi.2018.8363531","title":"Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection","display_name":"Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2806086905","doi":"https://doi.org/10.1109/isbi.2018.8363531","mag":"2806086905","pmid":"https://pubmed.ncbi.nlm.nih.gov/33014282"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7532925","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074139667","display_name":"Juntang Zhuang","orcid":"https://orcid.org/0000-0001-6466-8470"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Juntang Zhuang","raw_affiliation_strings":["Biomedical Engineering, Yale University, New Haven, CT USA","Biomedical Engineering, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Biomedical Engineering, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030309917","display_name":"Nicha C. Dvornek","orcid":"https://orcid.org/0000-0002-1648-6055"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicha C. Dvornek","raw_affiliation_strings":["Child Study Center, Yale University, New Haven, CT USA","Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT USA","Child Study Center, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458657","display_name":"Xiaoxiao Li","orcid":"https://orcid.org/0000-0002-8833-0244"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoxiao Li","raw_affiliation_strings":["Biomedical Engineering, Yale University, New Haven, CT USA","Biomedical Engineering, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Biomedical Engineering, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060593431","display_name":"Daniel Y.\u2010J. Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Yang","raw_affiliation_strings":["Autism and Neurodevelopmental Disorders Institute, The George Washington Univiersity, DC, USA","Child Study Center, Yale University, New Haven, CT USA","Child Study Center, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Autism and Neurodevelopmental Disorders Institute, The George Washington Univiersity, DC, USA","institution_ids":[]},{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007566576","display_name":"Pamela Ventola","orcid":"https://orcid.org/0000-0002-8062-0626"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pamela Ventola","raw_affiliation_strings":["Child Study Center, Yale University, New Haven, CT USA","Child Study Center, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Child Study Center, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046673670","display_name":"James S. Duncan","orcid":"https://orcid.org/0000-0002-5167-9856"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James S. Duncan","raw_affiliation_strings":["Biomedical Engineering, Yale University, New Haven, CT USA","Electrical Engineering, Yale University, New Haven, CT USA","Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT USA","Yale University, New Haven, CT, US"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Electrical Engineering, Yale University, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT USA","institution_ids":[]},{"raw_affiliation_string":"Yale University, New Haven, CT, US","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5074139667"],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":1.2345,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.7760495,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"97","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10106","display_name":"Autism Spectrum Disorder Research","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10106","display_name":"Autism Spectrum Disorder Research","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.780645489692688},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.6866787075996399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.587212324142456},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5706026554107666},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5465299487113953},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5345482230186462},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5270795226097107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.513922929763794},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4545549154281616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39281055331230164},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3322099447250366},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19056054949760437},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10915631055831909}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.780645489692688},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.6866787075996399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.587212324142456},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5706026554107666},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5465299487113953},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5345482230186462},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5270795226097107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.513922929763794},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4545549154281616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39281055331230164},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3322099447250366},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19056054949760437},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10915631055831909},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isbi.2018.8363531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},{"id":"pmid:33014282","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33014282","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:pubmedcentral.nih.gov:7532925","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7532925","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:7532925","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7532925","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2006096283","https://openalex.org/W2019482671","https://openalex.org/W2020299403","https://openalex.org/W2084754661","https://openalex.org/W2091028497","https://openalex.org/W2097176879","https://openalex.org/W2097576183","https://openalex.org/W2146437136","https://openalex.org/W2147791601","https://openalex.org/W2180390996","https://openalex.org/W2206641237","https://openalex.org/W2552482066","https://openalex.org/W2804685398","https://openalex.org/W4234063125","https://openalex.org/W4240064171","https://openalex.org/W6674382832","https://openalex.org/W6752164674"],"related_works":["https://openalex.org/W2978999882","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W1517228774","https://openalex.org/W2117019857","https://openalex.org/W3043435145"],"abstract_inverted_index":{"Behavior":[0],"intervention":[1],"has":[2],"shown":[3],"promise":[4],"for":[5,7,38,88,117],"treatment":[6],"young":[8],"children":[9,184],"with":[10,57,150,185],"autism":[11],"spectrum":[12],"disorder":[13],"(ASD).":[14],"However,":[15],"current":[16],"therapeutic":[17],"decisions":[18],"are":[19,125,156,160],"based":[20,45,133],"on":[21,46,65,134,179],"trial":[22],"and":[23,52,127,140,171,190],"error,":[24],"often":[25],"leading":[26],"to":[27,68,77,102,111,192],"suboptimal":[28],"outcomes.":[29],"We":[30,167],"propose":[31,93],"an":[32],"approach":[33],"that":[34],"employs":[35],"task-based":[36],"fMRI":[37],"early":[39],"outcome":[40],"prediction.":[41,90,118],"Our":[42,175],"strategy":[43],"is":[44,63,86,138,146],"the":[47,78,135,154],"general":[48],"linear":[49],"model":[50],"(GLM)":[51],"a":[53,94,99,108,180],"random":[54,123,136],"forest,":[55],"combined":[56],"feature":[58,84,96],"selection":[59,85,97,165],"techniques.":[60],"GLM":[61],"analysis":[62],"performed":[64],"each":[66,144],"voxel":[67],"get":[69],"t-statistic":[70],"of":[71,81,115,122,143,182],"contrast":[72],"between":[73],"two":[74],"tasks.":[75],"Due":[76],"high":[79],"dimensionality":[80],"predictor":[82],"variables,":[83,105],"crucial":[87],"accurate":[89],"Thus":[91],"we":[92],"two-step":[95],"method:":[98],"\"shadow\"":[100],"method":[101,110,176],"select":[103,112],"all-relevant":[104],"followed":[106],"by":[107],"stepwise":[109,163,173],"minimal-optimal":[113],"set":[114],"variables":[116],"A":[119],"few":[120],"columns":[121],"noise":[124],"generated":[126,200],"added":[128],"as":[129],"shadow":[130,155],"variables.":[131],"Regression":[132],"forest":[137],"performed,":[139],"permutation":[141],"importance":[142,152],"variable":[145,164],"estimated.":[147],"Candidate":[148],"voxels":[149,159],"higher":[151],"than":[153],"kept.":[157],"Surviving":[158],"fed":[161],"into":[162],"methods.":[166,196],"test":[168],"both":[169],"forward":[170],"backward":[172],"selection.":[174],"was":[177],"validated":[178],"dataset":[181],"20":[183],"ASD":[186],"using":[187],"leave-one-out":[188],"cross-validation,":[189],"compared":[191],"other":[193],"standard":[194],"regression":[195],"The":[197],"proposed":[198],"pipeline":[199],"highest":[201],"accuracy.":[202]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
