{"id":"https://openalex.org/W3201927123","doi":"https://doi.org/10.1145/3474906.3474912","title":"Helicobacter Pylori Infection Classification Based on Convolutional Neural Network and Self-Supervised Learning","display_name":"Helicobacter Pylori Infection Classification Based on Convolutional Neural Network and Self-Supervised Learning","publication_year":2021,"publication_date":"2021-06-25","ids":{"openalex":"https://openalex.org/W3201927123","doi":"https://doi.org/10.1145/3474906.3474912","mag":"3201927123"},"language":"en","primary_location":{"id":"doi:10.1145/3474906.3474912","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474906.3474912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Graphics and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5087777404","display_name":"Guo-Zhang Jian","orcid":null},"institutions":[{"id":"https://openalex.org/I65446980","display_name":"National Chin-Yi University of Technology","ror":"https://ror.org/040bs6h16","country_code":"TW","type":"education","lineage":["https://openalex.org/I65446980"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Guo-Zhang Jian","raw_affiliation_strings":["National Chin-Yi University of Technology, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chin-Yi University of Technology, Taiwan","institution_ids":["https://openalex.org/I65446980"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023487478","display_name":"Guo-Shiang Lin","orcid":"https://orcid.org/0000-0003-3422-2683"},"institutions":[{"id":"https://openalex.org/I65446980","display_name":"National Chin-Yi University of Technology","ror":"https://ror.org/040bs6h16","country_code":"TW","type":"education","lineage":["https://openalex.org/I65446980"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Guo-Shiang Lin","raw_affiliation_strings":["National Chin-Yi University of Technology, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chin-Yi University of Technology, Taiwan","institution_ids":["https://openalex.org/I65446980"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068516558","display_name":"Chuin-Mu Wang","orcid":"https://orcid.org/0000-0001-8137-3666"},"institutions":[{"id":"https://openalex.org/I65446980","display_name":"National Chin-Yi University of Technology","ror":"https://ror.org/040bs6h16","country_code":"TW","type":"education","lineage":["https://openalex.org/I65446980"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chuin-Mu Wang","raw_affiliation_strings":["National Chin-Yi University of Technology, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chin-Yi University of Technology, Taiwan","institution_ids":["https://openalex.org/I65446980"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078744722","display_name":"Sheng\u2010Lei Yan","orcid":"https://orcid.org/0000-0003-4305-8520"},"institutions":[{"id":"https://openalex.org/I4210124028","display_name":"Chang Bing Show Chwan Memorial Hospital","ror":"https://ror.org/02ntc9t93","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210124028"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sheng-Lei Yan","raw_affiliation_strings":["Chang Bing Show Chwan Memorial Hospital, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang Bing Show Chwan Memorial Hospital, Taiwan","institution_ids":["https://openalex.org/I4210124028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.7103,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94646554,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"60","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10276","display_name":"Helicobacter pylori-related gastroenterology studies","score":0.9927999973297119,"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/T10276","display_name":"Helicobacter pylori-related gastroenterology studies","score":0.9927999973297119,"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/T11316","display_name":"Mycobacterium research and diagnosis","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9465000033378601,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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":0.8270185589790344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7554055452346802},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6661280393600464},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6125321984291077},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.558398962020874},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5183064341545105},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5075565576553345},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4942770004272461},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4874289333820343},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43272507190704346},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.432207316160202},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4227745831012726},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40362632274627686},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3799387812614441}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8270185589790344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7554055452346802},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6661280393600464},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6125321984291077},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.558398962020874},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5183064341545105},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5075565576553345},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4942770004272461},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4874289333820343},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43272507190704346},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.432207316160202},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4227745831012726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40362632274627686},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3799387812614441},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474906.3474912","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474906.3474912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Graphics and Signal Processing","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":13,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1997715283","https://openalex.org/W2156290208","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2765095566","https://openalex.org/W2785325870","https://openalex.org/W2785825652","https://openalex.org/W2801817702","https://openalex.org/W2922479519","https://openalex.org/W2963426332","https://openalex.org/W2967784235","https://openalex.org/W2997235526"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W3181322968","https://openalex.org/W4292947472","https://openalex.org/W2995001409","https://openalex.org/W4360783045","https://openalex.org/W4212887358","https://openalex.org/W4322746360"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,29,112,132],"computer-aided":[4],"diagnosis":[5],"(CAD)":[6],"method":[7,22,107],"based":[8,88],"on":[9,89],"self-supervised":[10,39,154],"learning":[11,40],"was":[12],"proposed":[13,21,68,106],"for":[14,75,95,149],"helicobacter":[15],"pylori":[16],"(HP)":[17],"infection":[18,151],"classification.":[19],"The":[20,32,101,136],"is":[23],"composed":[24,108],"of":[25,66,84,109],"an":[26],"encoder":[27,33],"and":[28,41,93,97,111,127],"prediction":[30,50],"head.":[31],"can":[34,52,116,130,142],"be":[35,53],"trained":[36,47,54],"by":[37,55],"using":[38,56],"contrastive":[42,155],"loss.":[43],"After":[44],"obtaining":[45],"the":[46,49,57,64,67,81,85,105],"encoder,":[48],"head":[51],"small":[58],"medical":[59,71],"image":[60],"dataset.":[61],"To":[62],"evaluate":[63],"performance":[65],"method,":[69],"some":[70],"images":[72,119,122,148],"are":[73,91],"collected":[74],"testing.":[76],"According":[77],"to":[78],"experimental":[79,137],"results,":[80],"F1-score":[82],"rates":[83],"CAD":[86],"system":[87],"VGGNet-16":[90,110,129],"0.89":[92],"0.9":[94],"HP+":[96,118],"HP-":[98,121],"images,":[99],"respectively.":[100],"results":[102,138],"show":[103,139],"that":[104,140],"multi-layer":[113],"neural":[114],"network":[115],"distinguish":[117],"from":[120,146],"well.":[123],"Compared":[124],"with":[125],"ResNet-50":[126],"InceptionV3,":[128],"achieve":[131],"better":[133],"classification":[134,152],"performance.":[135],"VGG-16":[141],"extract":[143],"useful":[144],"features":[145],"endoscopic":[147],"HP":[150],"via":[153],"learning.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}