{"id":"https://openalex.org/W4379740407","doi":"https://doi.org/10.1109/iconstem56934.2023.10142317","title":"Early Detection and Quantification of Osteoarthritis Severity in Knee Using Support Vector Machine with Improved Accuracy Compared to Convolutional Neural Network","display_name":"Early Detection and Quantification of Osteoarthritis Severity in Knee Using Support Vector Machine with Improved Accuracy Compared to Convolutional Neural Network","publication_year":2023,"publication_date":"2023-04-06","ids":{"openalex":"https://openalex.org/W4379740407","doi":"https://doi.org/10.1109/iconstem56934.2023.10142317"},"language":"en","primary_location":{"id":"doi:10.1109/iconstem56934.2023.10142317","doi":"https://doi.org/10.1109/iconstem56934.2023.10142317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iconstem56934.2023.10142317","pdf_url":null,"source":{"id":"https://openalex.org/S7407086778","display_name":"International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W4379740407"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"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/A5104126156","display_name":"K. Sagar Raju","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. Sagar Raju","raw_affiliation_strings":["SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003768203","display_name":"V. Amudha","orcid":"https://orcid.org/0000-0002-0877-5260","observed_orcids":["https://orcid.org/0000-0002-0877-5260"]},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Amudha","raw_affiliation_strings":["SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068774476","display_name":"Natarajan Meenakshisundaram","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Meenakshisundaram. N","raw_affiliation_strings":["SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIMATS,Saveetha School of Engineering,Department of Electronics and Communication,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of Electronics and Communication, Saveetha School of Engineering, SIMATS, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I85461943"],"apc_list":null,"apc_paid":null,"fwci":1.3562,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78793566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.26030001044273376,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.26030001044273376,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.21299999952316284,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.1031000018119812,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/knee-osteoarthritis","display_name":"knee osteoarthritis","score":0.9929999709129333},{"id":"https://openalex.org/keywords/early-detection","display_name":"early detection","score":0.9340000152587891},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9769999980926514},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9890000224113464},{"id":"https://openalex.org/keywords/classifier-accuracy-comparison","display_name":"classifier accuracy comparison","score":0.6620000004768372},{"id":"https://openalex.org/keywords/knee-imaging","display_name":"knee imaging","score":0.3720000088214874}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8184871673583984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6167185306549072},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.611272931098938},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6025230288505554},{"id":"https://openalex.org/C191988596","wikidata":"https://www.wikidata.org/wiki/Q628374","display_name":"Null hypothesis","level":2,"score":0.5817498564720154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5766462683677673},{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.4715569019317627},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.46702292561531067},{"id":"https://openalex.org/C65409693","wikidata":"https://www.wikidata.org/wiki/Q425265","display_name":"Statistical significance","level":2,"score":0.4545738399028778},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4396764039993286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4338018000125885},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42976707220077515},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3550340533256531},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3218143582344055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1893376111984253}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iconstem56934.2023.10142317","doi":"https://doi.org/10.1109/iconstem56934.2023.10142317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iconstem56934.2023.10142317","pdf_url":null,"source":{"id":"https://openalex.org/S7407086778","display_name":"International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.9476000070571899}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2804204591","https://openalex.org/W2916872998","https://openalex.org/W2921861522","https://openalex.org/W2936573766","https://openalex.org/W2997273696","https://openalex.org/W3001077607","https://openalex.org/W3016521582","https://openalex.org/W3021286010","https://openalex.org/W3084521418","https://openalex.org/W3091943846","https://openalex.org/W3104305579","https://openalex.org/W3116286104","https://openalex.org/W3135028703","https://openalex.org/W3138114698","https://openalex.org/W3139236016","https://openalex.org/W4221117806","https://openalex.org/W4226419023","https://openalex.org/W4280511266","https://openalex.org/W4285489743","https://openalex.org/W4286384831","https://openalex.org/W4289780755","https://openalex.org/W4290697790","https://openalex.org/W4293768892","https://openalex.org/W4295786373"],"related_works":["https://openalex.org/W2971301550","https://openalex.org/W4414928411","https://openalex.org/W2983531097","https://openalex.org/W2606645974","https://openalex.org/W2902060228","https://openalex.org/W2183543037","https://openalex.org/W2487523897","https://openalex.org/W2998041039","https://openalex.org/W2549053814","https://openalex.org/W4406984787"],"abstract_inverted_index":{"This":[0],"study":[1],"will":[2],"make":[3],"use":[4],"of":[5,28,32,40,66,72,94,101,125,135,141,150,155,186,201],"a":[6,20,55,64,122,138,147],"classifier":[7],"that":[8,57,104,158,167,176,216],"has":[9],"improved":[10],"accuracy":[11,185,200],"for":[12,22],"support":[13],"vector":[14],"machines":[15],"in":[16,54,85,92],"order":[17],"to":[18,78,192,208],"build":[19],"strategy":[21],"the":[23,34,51,70,73,81,88,105,143,159,168,177,187,199,202,217],"early":[24],"detection":[25],"and":[26,36,45,137],"quantification":[27],"osteoarthritis.":[29],"In":[30],"terms":[31],"both":[33],"Materials":[35],"Methods:":[37],"A":[38],"total":[39,65],"350":[41],"samples":[42,68],"were":[43,47],"taken,":[44],"those":[46],"split":[48],"up":[49],"between":[50],"two":[52],"groups":[53],"manner":[56],"was":[58,112,190,196,206],"completely":[59],"random.":[60],"Each":[61],"participant":[62],"received":[63],"175":[67],"during":[69],"course":[71],"study.":[74],"When":[75],"it":[76],"comes":[77],"Group":[79,95],"1,":[80,132],"SVM":[82,189],"algorithm":[83,90],"is":[84,91,108,162,171,179,219],"charge,":[86],"but":[87],"CNN":[89,203],"charge":[93],"2.":[96],"Results:":[97],"The":[98,152,165,184,211],"significance":[99,153,169,212],"value":[100,140,149,154,170,213],"0.197":[102,156],"indicates":[103,157,175,215],"null":[106,160],"hypothesis":[107,161,178,218],"correct":[109,163,180],"(p>0.01);":[110],"this":[111],"determined":[113,191,207],"by":[114],"using":[115],"an":[116,127],"independent":[117],"sample":[118],"T":[119],"test":[120,144],"with":[121],"confidence":[123],"interval":[124],"95%,":[126],"enrolment":[128],"ratio":[129],"defined":[130],"as":[131],"g":[133],"power":[134],"80%,":[136],"threshold":[139,148],"0.5G;":[142],"also":[145,214],"includes":[146],"0.5G.":[151],"(p>0.01).":[164],"fact":[166],"greater":[172],"than":[173,198],"0.01":[174],"(p":[181],">":[182],"0.01);":[183],"innovative":[188],"be":[193,209],"87%,":[194],"which":[195,205],"higher":[197],"algorithm,":[204],"83%.":[210],"correct.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2023-06-08T00:00:00"}
