{"id":"https://openalex.org/W4406328976","doi":"https://doi.org/10.1145/3706890.3706964","title":"An Optimized Multilayer Perceptron Model for Disease Risk Prediction in Psychiatric and Psychological Nursing","display_name":"An Optimized Multilayer Perceptron Model for Disease Risk Prediction in Psychiatric and Psychological Nursing","publication_year":2024,"publication_date":"2024-08-13","ids":{"openalex":"https://openalex.org/W4406328976","doi":"https://doi.org/10.1145/3706890.3706964"},"language":"en","primary_location":{"id":"doi:10.1145/3706890.3706964","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3706890.3706964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 5th International Symposium on Artificial Intelligence for Medicine Science","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/A5100842389","display_name":"Yingjie Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127460","display_name":"Ningxia Medical University","ror":"https://ror.org/02h8a1848","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210127460"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingjie Zheng","raw_affiliation_strings":["College of Nursing, Ningxia Medical University, Yinchuan, Ningxia, China"],"raw_orcid":"https://orcid.org/0009-0007-6242-3294","affiliations":[{"raw_affiliation_string":"College of Nursing, Ningxia Medical University, Yinchuan, Ningxia, China","institution_ids":["https://openalex.org/I4210127460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115596323","display_name":"Xiaohui Liu","orcid":"https://orcid.org/0000-0002-1329-5405"},"institutions":[{"id":"https://openalex.org/I4210127460","display_name":"Ningxia Medical University","ror":"https://ror.org/02h8a1848","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210127460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Liu","raw_affiliation_strings":["College of Nursing, Ningxia Medical University, Yinchuan, Ningxia, China"],"raw_orcid":"https://orcid.org/0000-0002-1329-5405","affiliations":[{"raw_affiliation_string":"College of Nursing, Ningxia Medical University, Yinchuan, Ningxia, China","institution_ids":["https://openalex.org/I4210127460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100842389"],"corresponding_institution_ids":["https://openalex.org/I4210127460"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22730302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"426","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9958999752998352,"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/T10862","display_name":"AI in cancer detection","score":0.9958999752998352,"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":0.9958999752998352,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5722988843917847},{"id":"https://openalex.org/keywords/psychiatric-disease","display_name":"Psychiatric Disease","score":0.43538615107536316},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.4197857081890106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40539494156837463},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.36073797941207886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32227057218551636},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.321382611989975},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2987200915813446},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28944525122642517}],"concepts":[{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5722988843917847},{"id":"https://openalex.org/C2908876842","wikidata":"https://www.wikidata.org/wiki/Q12135","display_name":"Psychiatric Disease","level":3,"score":0.43538615107536316},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.4197857081890106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40539494156837463},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.36073797941207886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32227057218551636},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.321382611989975},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2987200915813446},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28944525122642517},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3706890.3706964","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3706890.3706964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 5th International Symposium on Artificial Intelligence for Medicine Science","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2664267452","https://openalex.org/W2747590145","https://openalex.org/W2908201961","https://openalex.org/W2912581524","https://openalex.org/W3012665221"],"related_works":["https://openalex.org/W3188962172","https://openalex.org/W2174939924","https://openalex.org/W2426023813","https://openalex.org/W1979272772","https://openalex.org/W2082130542","https://openalex.org/W2063396851","https://openalex.org/W4240454807","https://openalex.org/W1990409264","https://openalex.org/W1568537700","https://openalex.org/W2978743310"],"abstract_inverted_index":{"In":[0],"psychiatric":[1,158],"and":[2,16,41,57,72,84,105,111,120,137,146,166],"psychological":[3],"nursing,":[4,159],"the":[5,98,127],"early":[6],"identification":[7],"of":[8,142],"high-risk":[9,40],"individuals":[10],"is":[11],"essential":[12],"for":[13,44,154,163],"implementing":[14],"timely":[15],"personalized":[17,167],"interventions.":[18,170],"This":[19,148],"paper":[20],"presents":[21],"a":[22,29,161],"disease":[23,73],"risk":[24,155],"prediction":[25],"model":[26,48,91,94,129],"based":[27],"on":[28],"Multilayer":[30],"Perceptron":[31],"(MLP)":[32],"neural":[33],"network,":[34],"designed":[35],"to":[36,60,89,101,117],"classify":[37],"patients":[38],"into":[39],"low-risk":[42],"categories":[43],"multiple":[45],"diseases.":[46],"The":[47,93],"leverages":[49],"patient":[50,168],"data,":[51],"including":[52],"age,":[53],"gender,":[54],"medical":[55],"history,":[56],"medication":[58],"usage,":[59],"perform":[61],"multi-label":[62],"classification,":[63],"effectively":[64],"capturing":[65],"complex":[66],"nonlinear":[67],"relationships":[68],"between":[69],"input":[70],"features":[71],"risks.":[74],"Data":[75],"preprocessing":[76],"techniques,":[77],"such":[78],"as":[79],"handling":[80],"missing":[81],"values,":[82],"normalization,":[83],"feature":[85],"selection,":[86],"were":[87,115],"applied":[88],"improve":[90],"performance.":[92],"was":[95],"trained":[96],"using":[97],"Adam":[99],"optimizer":[100],"ensure":[102],"rapid":[103],"convergence":[104],"robust":[106],"learning,":[107],"while":[108],"L2":[109],"regularization":[110],"mini-batch":[112],"gradient":[113],"descent":[114],"employed":[116],"enhance":[118],"generalization":[119],"prevent":[121],"overfitting.":[122],"Experimental":[123],"results":[124],"indicate":[125],"that":[126],"MLP":[128],"significantly":[130],"outperforms":[131],"traditional":[132],"methods":[133],"like":[134],"logistic":[135],"regression":[136],"random":[138],"forest":[139],"in":[140,157],"terms":[141],"accuracy,":[143],"precision,":[144],"recall,":[145],"F1-score.":[147],"study":[149],"offers":[150],"an":[151],"advanced":[152],"tool":[153],"assessment":[156],"providing":[160],"foundation":[162],"more":[164],"accurate":[165],"care":[169]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}