{"id":"https://openalex.org/W4205728591","doi":"https://doi.org/10.1109/bigdata52589.2021.9671562","title":"A Distributed Deep Learning Framework for Federated Big Medical Image Analysis","display_name":"A Distributed Deep Learning Framework for Federated Big Medical Image Analysis","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205728591","doi":"https://doi.org/10.1109/bigdata52589.2021.9671562"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671562","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5101973211","display_name":"Soumya Snigdha Kundu","orcid":"https://orcid.org/0000-0002-4130-7725"},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Soumya Snigdha Kundu","raw_affiliation_strings":["SRM Institute of Science and Technology, Kattankulathur, India"],"affiliations":[{"raw_affiliation_string":"SRM Institute of Science and Technology, Kattankulathur, India","institution_ids":["https://openalex.org/I145286018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101973211"],"corresponding_institution_ids":["https://openalex.org/I145286018"],"apc_list":null,"apc_paid":null,"fwci":0.6043,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60334347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5938","last_page":"5940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9975000023841858,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9975000023841858,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9937999844551086,"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":0.9905999898910522,"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/computer-science","display_name":"Computer science","score":0.8259797692298889},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6963542699813843},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6652606129646301},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5894918441772461},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.587965726852417},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5709402561187744},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5554662942886353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46124333143234253},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3921402096748352},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3809710144996643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3617764413356781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8259797692298889},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6963542699813843},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6652606129646301},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5894918441772461},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.587965726852417},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5709402561187744},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5554662942886353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46124333143234253},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3921402096748352},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3809710144996643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3617764413356781},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671562","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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":34,"referenced_works":["https://openalex.org/W2119144962","https://openalex.org/W2295107390","https://openalex.org/W2346062110","https://openalex.org/W2559785631","https://openalex.org/W2766839578","https://openalex.org/W2901954625","https://openalex.org/W2963466845","https://openalex.org/W3013277995","https://openalex.org/W3016950572","https://openalex.org/W3027763298","https://openalex.org/W3035253074","https://openalex.org/W3036703963","https://openalex.org/W3037256687","https://openalex.org/W3091921149","https://openalex.org/W3095681026","https://openalex.org/W3112780421","https://openalex.org/W3125012172","https://openalex.org/W3126027909","https://openalex.org/W3135057764","https://openalex.org/W3149839747","https://openalex.org/W3166799498","https://openalex.org/W3210151345","https://openalex.org/W4220738117","https://openalex.org/W4300485340","https://openalex.org/W6677580257","https://openalex.org/W6697443983","https://openalex.org/W6745499037","https://openalex.org/W6746693533","https://openalex.org/W6779478644","https://openalex.org/W6784064631","https://openalex.org/W6788031218","https://openalex.org/W6790453207","https://openalex.org/W6793364036","https://openalex.org/W6794649757"],"related_works":["https://openalex.org/W4312200629","https://openalex.org/W4223943233","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W3014300295","https://openalex.org/W4309045103","https://openalex.org/W4225161397","https://openalex.org/W4312831135","https://openalex.org/W3166850502","https://openalex.org/W2949506716"],"abstract_inverted_index":{"The":[0],"use":[1,33],"of":[2,34],"big":[3],"data":[4,46],"in":[5,42],"medical":[6,45,58],"image":[7,59],"analysis":[8,60],"has":[9,28],"time":[10],"again":[11],"proved":[12],"to":[13,31,55],"advanced":[14],"the":[15,32],"field":[16],"by":[17],"generating":[18],"higher":[19],"diagnostic":[20],"accuracy":[21],"and":[22,38,68],"improved":[23],"neural":[24,36],"network":[25],"performance.":[26],"This":[27],"also":[29],"led":[30],"larger":[35],"networks":[37],"increased":[39],"security":[40],"risk":[41],"sharing":[43],"sensitive":[44],"information.":[47],"In":[48],"this":[49],"paper,":[50],"a":[51],"pipeline":[52],"is":[53],"theorised":[54],"securely":[56],"facilitate":[57],"through":[61],"reduced":[62],"computational":[63],"costs":[64],"using":[65],"federated":[66],"learning":[67],"model":[69],"compression":[70],"frameworks.":[71]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}