{"id":"https://openalex.org/W2119253000","doi":"https://doi.org/10.1080/019697200124775","title":"SELECTION OF SURGICAL RESIDENTS: A NEURAL NETWORK APPROACH","display_name":"SELECTION OF SURGICAL RESIDENTS: A NEURAL NETWORK APPROACH","publication_year":2000,"publication_date":"2000-06-01","ids":{"openalex":"https://openalex.org/W2119253000","doi":"https://doi.org/10.1080/019697200124775","mag":"2119253000"},"language":"en","primary_location":{"id":"doi:10.1080/019697200124775","is_oa":false,"landing_page_url":"https://doi.org/10.1080/019697200124775","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and 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/A5100886813","display_name":"Steven D. Travers Ajay K. Aggarwal","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ajay K. Aggarwal, Steven D. Travers","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100886813"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.17509677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"4","first_page":"417","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.9430999755859375,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.9430999755859375,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11930","display_name":"Cardiac, Anesthesia and Surgical Outcomes","score":0.9070000052452087,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/selection","display_name":"Selection (genetic algorithm)","score":0.7516650557518005},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.7474327087402344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.747177004814148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6867252588272095},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6657569408416748},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5973408818244934},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5807586908340454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5776494145393372},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5750241279602051},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4930822551250458},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.329243004322052}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7516650557518005},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.7474327087402344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.747177004814148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6867252588272095},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6657569408416748},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5973408818244934},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5807586908340454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5776494145393372},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5750241279602051},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4930822551250458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.329243004322052},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/019697200124775","is_oa":false,"landing_page_url":"https://doi.org/10.1080/019697200124775","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W178231042","https://openalex.org/W2360028903","https://openalex.org/W4280543773","https://openalex.org/W1966421350","https://openalex.org/W2366083136","https://openalex.org/W2387622493","https://openalex.org/W1868434454"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"criteria":[2,20],"used":[3],"by":[4],"program":[5],"directors":[6],"in":[7,50,77],"surgery":[8],"for":[9],"selection":[10,42,64],"of":[11,32],"surgical":[12,62],"residents":[13,63],"varies":[14],"widely":[15],"across":[16],"programs.":[17],"While":[18],"most":[19],"tends":[21],"to":[22,39,59,75],"include":[23],"one":[24],"or":[25],"more":[26],"interviews,":[27],"grades,":[28],"experience,":[29],"and":[30,44],"letters":[31],"recommendation,":[33],"there":[34],"are":[35,48,73],"very":[36],"few":[37],"models":[38],"facilitate":[40,60],"the":[41,45,61],"process,":[43],"existing":[46],"ones":[47],"linear":[49],"scope.":[51],"This":[52],"paper":[53],"presents":[54],"a":[55,85],"neural":[56],"network":[57],"approach":[58],"process":[65],"using":[66,84],"36":[67],"variables.":[68],"Multi-layer":[69],"perceptrons":[70],"employing":[71],"backpropagation":[72],"shown":[74],"result":[76],"better":[78],"separation":[79],"than":[80],"stepwise":[81],"discriminant":[82],"analysis":[83],"paired":[86],"t-test.":[87]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}