{"id":"https://openalex.org/W4408519699","doi":"https://doi.org/10.59670/ml.v21is14.11625","title":"Predicting Cardiovascular Outcomes: A Comparative Study Of Bayesian And Traditional Methods","display_name":"Predicting Cardiovascular Outcomes: A Comparative Study Of Bayesian And Traditional Methods","publication_year":2024,"publication_date":"2024-09-05","ids":{"openalex":"https://openalex.org/W4408519699","doi":"https://doi.org/10.59670/ml.v21is14.11625"},"language":"en","primary_location":{"id":"doi:10.59670/ml.v21is14.11625","doi":"https://doi.org/10.59670/ml.v21is14.11625","is_oa":true,"landing_page_url":"https://doi.org/10.59670/ml.v21is14.11625","pdf_url":"https://migrationletters.com/index.php/ml/article/download/11625/7763","source":{"id":"https://openalex.org/S91849133","display_name":"MIGRATION LETTERS","issn_l":"1741-8984","issn":["1741-8984","1741-8992"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Migration Letters","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://migrationletters.com/index.php/ml/article/download/11625/7763","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013302650","display_name":"Muhammad Muzammal Murtaza","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hafiz Bilal Murtaza,  Muhammad Zafar Iqbal, Muhammad Kashif, Madiha Ghamkha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5013302650"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34846667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":"S14","first_page":"1018","last_page":"1029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":1.0,"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":1.0,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.0,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cardiovascular-disease-prediction","display_name":"cardiovascular disease prediction","score":0.9139999747276306},{"id":"https://openalex.org/keywords/bayesian-model","display_name":"Bayesian model","score":0.718999981880188},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.8899999856948853},{"id":"https://openalex.org/keywords/decision-tree","display_name":"decision tree","score":0.996999979019165},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.796999990940094},{"id":"https://openalex.org/keywords/prediction-accuracy","display_name":"prediction accuracy","score":0.5669999718666077},{"id":"https://openalex.org/keywords/model-interpretability","display_name":"model interpretability","score":0.781000018119812},{"id":"https://openalex.org/keywords/clinical-and-demographic-data","display_name":"clinical and demographic data","score":0.7749999761581421}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5741793513298035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4384775757789612},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4070166349411011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2789660096168518},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.19742771983146667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.59670/ml.v21is14.11625","doi":"https://doi.org/10.59670/ml.v21is14.11625","is_oa":true,"landing_page_url":"https://doi.org/10.59670/ml.v21is14.11625","pdf_url":"https://migrationletters.com/index.php/ml/article/download/11625/7763","source":{"id":"https://openalex.org/S91849133","display_name":"MIGRATION LETTERS","issn_l":"1741-8984","issn":["1741-8984","1741-8992"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Migration Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.59670/ml.v21is14.11625","doi":"https://doi.org/10.59670/ml.v21is14.11625","is_oa":true,"landing_page_url":"https://doi.org/10.59670/ml.v21is14.11625","pdf_url":"https://migrationletters.com/index.php/ml/article/download/11625/7763","source":{"id":"https://openalex.org/S91849133","display_name":"MIGRATION LETTERS","issn_l":"1741-8984","issn":["1741-8984","1741-8992"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"Migration Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.9391000270843506,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408519699.pdf","grobid_xml":"https://content.openalex.org/works/W4408519699.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0],"study":[1,117],"comprehensively":[2],"examines":[3],"and":[4,24,36,43,59,71,80,84,113,120,131,140],"compares":[5],"current":[6],"heart":[7,29,102,132],"disease":[8,103,133],"prediction":[9],"systems,":[10],"focusing":[11],"on":[12],"Bayesian":[13,54,83,112],"techniques":[14,86],"versus":[15],"conventional":[16],"methods.":[17],"We":[18,32,74],"aim":[19],"to":[20,40,65,87,98,127],"determine":[21],"their":[22,89],"effectiveness":[23],"ease":[25],"of":[26,82],"interpretation":[27],"in":[28,138],"health":[30],"prognosis.":[31],"use":[33],"various":[34],"statistical":[35],"machine":[37],"learning":[38],"models":[39],"analyze":[41,94],"clinical":[42],"demographic":[44],"data":[45],"from":[46],"a":[47],"large":[48],"patient":[49,129,143],"population":[50],"collected":[51],"over":[52],"time.":[53],"approaches,":[55],"which":[56],"handle":[57],"uncertainty":[58],"complex":[60],"variable":[61],"interactions,":[62],"are":[63],"compared":[64],"simpler":[66],"methods":[67,126],"like":[68],"logistic":[69],"regression":[70],"decision":[72],"trees.":[73],"assess":[75],"the":[76,95],"accuracy,":[77],"sensitivity,":[78],"specificity,":[79],"AUC-ROC":[81],"traditional":[85,114],"evaluate":[88],"predictive":[90,136],"performance.":[91],"Additionally,":[92],"we":[93],"models'":[96],"ability":[97],"explain":[99],"factors":[100],"influencing":[101],"outcomes,":[104],"crucial":[105],"for":[106],"informed":[107],"treatment":[108],"decisions.":[109],"By":[110],"comparing":[111],"methodologies,":[115],"this":[116],"helps":[118],"academics":[119],"healthcare":[121,139],"practitioners":[122],"identify":[123],"optimal":[124],"modeling":[125],"enhance":[128],"care":[130],"survival,":[134],"advancing":[135],"analytics":[137],"improving":[141],"cardiovascular":[142],"management.":[144]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
