{"id":"https://openalex.org/W4388599731","doi":"https://doi.org/10.1016/j.heliyon.2023.e22283","title":"DLSDHMS: Design of a deep learning-based analysis model for secure and distributed hospital management using context-aware sidechains","display_name":"DLSDHMS: Design of a deep learning-based analysis model for secure and distributed hospital management using context-aware sidechains","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4388599731","doi":"https://doi.org/10.1016/j.heliyon.2023.e22283","pmid":"https://pubmed.ncbi.nlm.nih.gov/38034655","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/10687239"},"language":"en","primary_location":{"id":"doi:10.1016/j.heliyon.2023.e22283","doi":"https://doi.org/10.1016/j.heliyon.2023.e22283","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e22283","pdf_url":null,"source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Heliyon","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.heliyon.2023.e22283","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Vonteru Srikanth Reddy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4401726783","display_name":"VIT-AP University","ror":"https://ror.org/007v4hf75","country_code":"IN","type":"education","lineage":["https://openalex.org/I4401726783"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vonteru Srikanth Reddy","raw_affiliation_strings":["School of Computer Science and Engineering, VIT-AP University, Amaravati, 522237, Andhra Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, VIT-AP University, Amaravati, 522237, Andhra Pradesh, India","institution_ids":["https://openalex.org/I4401726783"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012048624","display_name":"Kumar Debasis","orcid":"https://orcid.org/0000-0002-0352-3267","observed_orcids":["https://orcid.org/0000-0002-0352-3267"]},"institutions":[{"id":"https://openalex.org/I4401726783","display_name":"VIT-AP University","ror":"https://ror.org/007v4hf75","country_code":"IN","type":"education","lineage":["https://openalex.org/I4401726783"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Kumar Debasis","raw_affiliation_strings":["School of Computer Science and Engineering, VIT-AP University, Amaravati, 522237, Andhra Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, VIT-AP University, Amaravati, 522237, Andhra Pradesh, India","institution_ids":["https://openalex.org/I4401726783"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012048624"],"corresponding_institution_ids":["https://openalex.org/I4401726783"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":0.7163,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72576874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"9","issue":"11","first_page":"e22283","last_page":"e22283"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13038","display_name":"Internet of Things and AI","score":0.004999999888241291,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.000699999975040555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hospital-management","display_name":"hospital management","score":0.9819999933242798},{"id":"https://openalex.org/keywords/distributed-healthcare","display_name":"distributed healthcare","score":0.3310000002384186},{"id":"https://openalex.org/keywords/iot-data-collection","display_name":"IoT data collection","score":0.515999972820282},{"id":"https://openalex.org/keywords/data-storage-optimization","display_name":"data storage optimization","score":0.5979999899864197},{"id":"https://openalex.org/keywords/appointment-management","display_name":"appointment management","score":0.7680000066757202},{"id":"https://openalex.org/keywords/disease-prediction","display_name":"disease prediction","score":0.7910000085830688},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.765999972820282},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9909999966621399},{"id":"https://openalex.org/keywords/secure-data-storage","display_name":"secure data storage","score":0.5789999961853027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7198992967605591},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6946201324462891},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5714163184165955},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.565702497959137},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.518168568611145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5119649171829224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4399508237838745},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.43517354130744934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42919641733169556},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3691132068634033},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35823577642440796},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.1712641417980194},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1016/j.heliyon.2023.e22283","doi":"https://doi.org/10.1016/j.heliyon.2023.e22283","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e22283","pdf_url":null,"source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Heliyon","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10687239","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10687239","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10687239/pdf/main.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Heliyon","raw_type":"Text"},{"id":"pmid:38034655","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38034655","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,"listed_in":[],"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":"Heliyon","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:1fc9c714046043b48773953a67fca87f","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/1fc9c714046043b48773953a67fca87f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Heliyon, Vol 9, Iss 11, Pp e22283- (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.heliyon.2023.e22283","doi":"https://doi.org/10.1016/j.heliyon.2023.e22283","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e22283","pdf_url":null,"source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Heliyon","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8048999905586243,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388599731.pdf","grobid_xml":"https://content.openalex.org/works/W4388599731.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W2556834368","https://openalex.org/W2717964723","https://openalex.org/W2769209708","https://openalex.org/W2774102979","https://openalex.org/W2800426337","https://openalex.org/W2884913753","https://openalex.org/W2889232559","https://openalex.org/W2903576096","https://openalex.org/W2912000072","https://openalex.org/W2915032385","https://openalex.org/W2915943648","https://openalex.org/W2942155209","https://openalex.org/W2945520341","https://openalex.org/W2953682518","https://openalex.org/W2980534764","https://openalex.org/W3000048986","https://openalex.org/W3000832017","https://openalex.org/W3002312215","https://openalex.org/W3017286598","https://openalex.org/W3019839747","https://openalex.org/W3028279553","https://openalex.org/W3029972659","https://openalex.org/W3035050356","https://openalex.org/W3041772532","https://openalex.org/W3091930004","https://openalex.org/W3092540620","https://openalex.org/W3094377329","https://openalex.org/W3094455654","https://openalex.org/W3094497160","https://openalex.org/W3094601420","https://openalex.org/W3094904458","https://openalex.org/W3097520799","https://openalex.org/W3105232160","https://openalex.org/W3107142181","https://openalex.org/W3113716289","https://openalex.org/W3121690322","https://openalex.org/W3175304747","https://openalex.org/W3175621169","https://openalex.org/W3183821682","https://openalex.org/W3184610124","https://openalex.org/W3194059928","https://openalex.org/W4206115374","https://openalex.org/W4220677855","https://openalex.org/W4281250833","https://openalex.org/W4283311065","https://openalex.org/W4308403919","https://openalex.org/W4383199523","https://openalex.org/W4383815892","https://openalex.org/W4386524476","https://openalex.org/W6801967701"],"related_works":["https://openalex.org/W3206288486","https://openalex.org/W6922609880","https://openalex.org/W4410117957","https://openalex.org/W4407628089","https://openalex.org/W7202044010","https://openalex.org/W3136356948","https://openalex.org/W4376862740","https://openalex.org/W4229007738","https://openalex.org/W4310009600","https://openalex.org/W4206961924"],"abstract_inverted_index":{"Designing":[0],"an":[1,107,142],"efficient":[2],"hospital":[3,30,90,104],"management":[4,31,91],"solution":[5],"requires":[6],"the":[7,77,112,198,204,215],"integration":[8],"of":[9,52,79,171,206,220],"multidomain":[10],"operations":[11],"that":[12,147,181],"include":[13],"secure":[14,87],"storage,":[15],"alert":[16],"system":[17],"modelling,":[18],"infrastructure":[19],"management,":[20,22],"staff":[21],"report":[23],"analysis,":[24,44],"and":[25,88,110,130,133,152,158,176,187,201,227,254],"feedback-based":[26],"learning":[27,43],"tasks.":[28],"Existing":[29],"models":[32,54],"are":[33,139],"either":[34],"highly":[35],"complex":[36],"or":[37],"do":[38],"not":[39],"incorporate":[40],"comprehensive":[41],"deep":[42,82],"which":[45,59,259],"limits":[46],"their":[47,61],"deployment":[48],"capabilities.":[49],"Moreover,":[50],"most":[51],"these":[53,72,164,193,213],"use":[55],"mutable":[56],"storage":[57,151,229],"solutions,":[58],"restricts":[60],"trust":[62],"levels":[63],"under":[64],"multi-patient":[65],"to":[66,124,212,236,245],"multi-doctor":[67],"mapping":[68],"scenarios.":[69],"To":[70],"overcome":[71],"issues,":[73],"this":[74],"article":[75],"proposes":[76],"design":[78],"a":[80,169],"novel":[81],"Learning-based":[83],"analysis":[84],"model":[85,96,217,241],"for":[86,208,263],"distributed":[89],"via":[92,106,141,155,168],"context-aware":[93],"sidechains.":[94,116],"The":[95,189,240],"initially":[97],"collects":[98],"large-scale":[99],"information":[100,113,121,190],"sets":[101,122],"from":[102,192],"different":[103],"entities":[105],"IoT-based":[108],"network":[109],"stores":[111],"on":[114,163,197],"context-sensitive":[115,118],"These":[117,137],"sidechains":[119],"store":[120],"related":[123],"Medicine":[125],"Management,":[126,128,132],"Doctor":[127],"Insurance":[129],"Billing":[131],"Appointment":[134],"Management":[135],"operations.":[136,160],"chains":[138,165],"optimized":[140],"Iterative":[143],"Genetic":[144],"Algorithm":[145],"(IGA)":[146],"assists":[148,202],"in":[149,183,203],"improving":[150],"retrieval":[153],"performance":[154],"intelligent":[156],"merging":[157],"splitting":[159],"Information":[161],"stored":[162],"is":[166,195,218,242],"processed":[167],"combination":[170],"Recurrent":[172],"Neural":[173,178],"Networks":[174,179],"(RNNs)":[175],"Convolutional":[177],"(CNNs),":[180],"assist":[182],"identifying":[184],"patient-level":[185],"diseases":[186,207],"issues.":[188],"obtained":[191],"classifiers":[194],"updated":[196],"central":[199],"repository":[200],"pre-emption":[205],"other":[209,237],"patients.":[210],"Due":[211],"integrations,":[214],"proposed":[216],"capable":[219],"reducing":[221,228],"computational":[222],"delay":[223],"by":[224,231],"3.5":[225],"%":[226,233,251,256],"cost":[230],"8.3":[232],"when":[234],"compared":[235],"blockchain-based":[238],"deployments.":[239,266],"also":[243],"able":[244],"pre-empt":[246],"patient":[247],"issues":[248],"with":[249],"9.3":[250],"higher":[252,257],"accuracy":[253],"4.8":[255],"precision,":[258],"makes":[260],"it":[261],"useful":[262],"real-time":[264],"clinical":[265]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-11-12T00:00:00"}