{"id":"https://openalex.org/W4399269677","doi":"https://doi.org/10.1016/j.procs.2024.04.278","title":"An Incremental Naive Bayes Learner for Real-time Health Prediction","display_name":"An Incremental Naive Bayes Learner for Real-time Health Prediction","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399269677","doi":"https://doi.org/10.1016/j.procs.2024.04.278"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2024.04.278","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2024.04.278","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Procedia Computer Science","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2024.04.278","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5098978490","display_name":"Deepthi Appasani","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepthi Appasani","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098978491","display_name":"Charan Sai Bokkisam","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Charan Sai Bokkisam","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034004706","display_name":"Simi Surendran","orcid":"https://orcid.org/0000-0001-7018-9476"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Simi Surendran","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5034004706"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":3.0195,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92766696,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"235","issue":null,"first_page":"2942","last_page":"2954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9210284948348999},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7540649175643921},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5770778656005859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5114508867263794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5109438300132751},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3394005000591278},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3072390556335449},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.14869743585586548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9210284948348999},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7540649175643921},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5770778656005859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5114508867263794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5109438300132751},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3394005000591278},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3072390556335449},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.14869743585586548}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2024.04.278","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2024.04.278","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2024.04.278","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2024.04.278","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1525647652","https://openalex.org/W1585854823","https://openalex.org/W1976606095","https://openalex.org/W1985602045","https://openalex.org/W2063816676","https://openalex.org/W2160512933","https://openalex.org/W2165743104","https://openalex.org/W2806091641","https://openalex.org/W2905012420","https://openalex.org/W2973623793","https://openalex.org/W2990525776","https://openalex.org/W3102015031","https://openalex.org/W3159812013","https://openalex.org/W3198714350","https://openalex.org/W3209788762","https://openalex.org/W3211228424","https://openalex.org/W4206207889","https://openalex.org/W4313072204","https://openalex.org/W4313887184","https://openalex.org/W4362681922","https://openalex.org/W6767636951","https://openalex.org/W6785333560","https://openalex.org/W6888853448","https://openalex.org/W6926533507"],"related_works":["https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2726838704","https://openalex.org/W4220802396","https://openalex.org/W1989494794","https://openalex.org/W2122031327","https://openalex.org/W1184238669","https://openalex.org/W2537862391","https://openalex.org/W2417174640","https://openalex.org/W3032901101"],"abstract_inverted_index":{"Healthcare":[0],"monitoring":[1,217],"systems":[2,218],"have":[3],"improved":[4],"with":[5],"the":[6,39,114,126,129,141,145,169,177,182,186],"Internet":[7],"of":[8,59,93,124,157,171,179,213],"Things":[9],"and":[10,30,68,138,160,198,202],"machine":[11],"learning":[12,54,162],"prediction":[13],"models.":[14],"Traditional":[15],"batch":[16,159],"machine-learning":[17],"approaches":[18],"cannot":[19],"generate":[20],"an":[21,75],"effective":[22],"model":[23,49,115],"since":[24,38],"most":[25],"data":[26,34,41,94,99,109],"will":[27],"be":[28],"continuous":[29,48],"real-time.":[31],"Real-time":[32],"medical":[33,166],"processing":[35,121],"is":[36,42,55,100,110],"challenging":[37],"entire":[40],"unavailable":[43],"during":[44],"prediction.":[45],"Here,":[46],"a":[47,61,90,135,149,154,209],"adaptation":[50],"based":[51],"on":[52,164],"incremental":[53,161,172],"demanded.":[56],"The":[57,87,102,132,174],"development":[58],"such":[60],"system":[62,133],"can":[63,81],"significantly":[64],"improve":[65],"patient":[66],"outcomes":[67],"reduce":[69],"healthcare":[70,216],"costs.":[71],"This":[72,206],"paper":[73],"proposes":[74],"Incremental":[76],"Naive":[77],"Bayes":[78],"Learner":[79],"that":[80],"handle":[82],"concept":[83,136,223],"drifts":[84],"in":[85,215],"data.":[86],"algorithm":[88,127],"keeps":[89],"sliding":[91],"window":[92,104],"constantly":[95],"updated":[96],"as":[97],"new":[98],"added.":[101],"adaptive":[103],"size":[105],"determines":[106],"how":[107],"much":[108],"used":[111],"to":[112],"train":[113],"at":[116,189,194],"any":[117],"given":[118],"time.":[119],"After":[120],"each":[122],"chunk":[123],"data,":[125],"calculates":[128],"model\u2019s":[130],"accuracy.":[131],"detects":[134],"drift":[137],"dynamically":[139],"updates":[140],"training":[142],"set":[143],"if":[144],"accuracy":[146,188,214],"drops":[147],"below":[148],"predefined":[150],"threshold.":[151],"We":[152],"conducted":[153],"comparative":[155],"evaluation":[156],"state-of-the-art":[158],"algorithms":[163],"different":[165],"datasets,":[167],"demonstrating":[168],"impact":[170],"learning.":[173],"results":[175],"demonstrate":[176],"effectiveness":[178],"our":[180],"approach:":[181],"Agrawal":[183],"dataset":[184],"achieved":[185,200],"highest":[187],"66.6%,":[190],"followed":[191],"by":[192],"Dialysis":[193],"61.6%,":[195],"while":[196],"Liver":[197],"HCC":[199],"50%":[201],"58.3%":[203],"accuracy,":[204],"respectively.":[205],"approach":[207],"ensures":[208],"sustained":[210],"high":[211],"level":[212],"over":[219],"time,":[220],"even":[221],"amidst":[222],"drift.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
