{"id":"https://openalex.org/W7216745810","doi":null,"title":"The Role of Artificial Intelligence in Improving Diagnostic Accuracy in Cardiology and Radiology: In-Depth Analysis of Ethical, Legal, and Clinical Implications across Multiple Medical Disciplines","display_name":"The Role of Artificial Intelligence in Improving Diagnostic Accuracy in Cardiology and Radiology: In-Depth Analysis of Ethical, Legal, and Clinical Implications across Multiple Medical Disciplines","publication_year":2024,"publication_date":"2024-10-19","ids":{"openalex":"https://openalex.org/W7216745810"},"language":"en","primary_location":{"id":"pmh:oai:ojs2.reviewofconphil.com:article/934","doi":null,"is_oa":true,"landing_page_url":"https://reviewofconphil.com/index.php/journal/article/view/934","pdf_url":"https://reviewofconphil.com/index.php/journal/article/download/934/953","source":{"id":"https://openalex.org/S4210206023","display_name":"Review of Contemporary Philosophy","issn_l":"1841-5261","issn":["1841-5261","2471-089X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["erih-plus","poland-70","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1841-5261","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://reviewofconphil.com/index.php/journal/article/download/934/953","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5154530309","display_name":" Ibrahim Hussain Alfenis","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ibrahim Hussain Alfenis,","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5154530309"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3371525,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.00019999999494757503,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":9.999999747378752e-05,"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/artificial-intelligence-in-healthcare","display_name":"artificial intelligence in healthcare","score":0.8190000057220459},{"id":"https://openalex.org/keywords/cardiovascular-imaging","display_name":"cardiovascular imaging","score":0.9810000061988831},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"diagnostic accuracy","score":0.8500000238418579},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.8069999814033508},{"id":"https://openalex.org/keywords/black-box-problem","display_name":"black box problem","score":0.7250000238418579},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7009999752044678},{"id":"https://openalex.org/keywords/clinical-ethics","display_name":"clinical ethics","score":0.40299999713897705},{"id":"https://openalex.org/keywords/legal-implications-of-ai","display_name":"legal implications of AI","score":0.8180000185966492},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.5849999785423279},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9710000157356262},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.9789999723434448},{"id":"https://openalex.org/keywords/coronary-stenosis-detection","display_name":"coronary stenosis detection","score":0.9789999723434448},{"id":"https://openalex.org/keywords/ct-angiography","display_name":"CT angiography","score":0.9210000038146973},{"id":"https://openalex.org/keywords/cardiovascular-event-prediction","display_name":"cardiovascular event prediction","score":0.9279999732971191},{"id":"https://openalex.org/keywords/clinical-workflow-efficiency","display_name":"clinical workflow efficiency","score":0.43799999356269836},{"id":"https://openalex.org/keywords/trust-in-ai","display_name":"trust in AI","score":0.7269999980926514}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8379999995231628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6876999735832214},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5710999965667725},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4634000062942505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44119998812675476},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.40149998664855957},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.3529999852180481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3174000084400177},{"id":"https://openalex.org/C2777120189","wikidata":"https://www.wikidata.org/wiki/Q780067","display_name":"Triage","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C2989236134","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Patient care","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C2778213512","wikidata":"https://www.wikidata.org/wiki/Q844935","display_name":"Coronary artery disease","level":2,"score":0.27320000529289246}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs2.reviewofconphil.com:article/934","doi":null,"is_oa":true,"landing_page_url":"https://reviewofconphil.com/index.php/journal/article/view/934","pdf_url":"https://reviewofconphil.com/index.php/journal/article/download/934/953","source":{"id":"https://openalex.org/S4210206023","display_name":"Review of Contemporary Philosophy","issn_l":"1841-5261","issn":["1841-5261","2471-089X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["erih-plus","poland-70","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1841-5261","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ojs2.reviewofconphil.com:article/934","doi":null,"is_oa":true,"landing_page_url":"https://reviewofconphil.com/index.php/journal/article/view/934","pdf_url":"https://reviewofconphil.com/index.php/journal/article/download/934/953","source":{"id":"https://openalex.org/S4210206023","display_name":"Review of Contemporary Philosophy","issn_l":"1841-5261","issn":["1841-5261","2471-089X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["erih-plus","poland-70","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1841-5261","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8999999761581421}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7216745810.pdf","grobid_xml":"https://content.openalex.org/works/W7216745810.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2273396394","https://openalex.org/W2894495420","https://openalex.org/W3128391547"],"related_works":["https://openalex.org/W4402524908","https://openalex.org/W4399153308","https://openalex.org/W4402129493","https://openalex.org/W4416723280","https://openalex.org/W7152478517","https://openalex.org/W6968261094","https://openalex.org/W7154573178","https://openalex.org/W7166686477","https://openalex.org/W7135071082","https://openalex.org/W7165767002"],"abstract_inverted_index":{"Background:":[0],"The":[1,94],"integration":[2,218],"of":[3,26,132,149,188,219],"Artificial":[4],"Intelligence":[5],"(AI)":[6],"within":[7],"cardiovascular":[8,62,122,143,178],"imaging":[9,105,126],"is":[10,196,213],"transforming":[11],"diagnostic":[12,108,175],"processes":[13,152],"across":[14],"medical":[15],"specialties,":[16],"particularly":[17,45],"in":[18,61,104,120,177,207],"cardiology,":[19],"radiology,":[20],"and":[21,35,42,49,71,83,88,110,124,139,194,203],"oncology.":[22],"However,":[23,145],"the":[24,66,89,146,163,180,186,216],"complexities":[25],"AI":[27,59,114,150,170,190,220],"models,":[28],"notably":[29],"those":[30],"utilizing":[31],"machine":[32],"learning":[33,37,75],"(ML)":[34],"deep":[36,74],"(DL),":[38],"raise":[39],"significant":[40],"ethical":[41,205],"legal":[43],"concerns,":[44],"regarding":[46],"their":[47],"interpretability":[48,195],"decision-making":[50],"transparency.":[51],"Methods:":[52],"This":[53],"review":[54],"synthesizes":[55],"existing":[56],"literature":[57],"on":[58,97],"applications":[60],"imaging.":[63],"It":[64],"examines":[65],"methodologies":[67],"employed,":[68],"including":[69],"supervised":[70],"unsupervised":[72],"learning,":[73],"frameworks":[76],"such":[77],"as":[78,156],"convolutional":[79],"neural":[80],"networks":[81,86],"(CNNs),":[82],"generative":[84],"adversarial":[85],"(GANs),":[87],"implications":[90],"for":[91,142,173,198,215],"clinical":[92,154,208],"practice.":[93],"analysis":[95],"focuses":[96],"AI's":[98],"ability":[99],"to":[100],"detect":[101],"subtle":[102],"patterns":[103],"data,":[106],"enhancing":[107],"accuracy":[109],"workflow":[111],"efficiency.":[112],"Results:":[113],"technologies":[115,221],"have":[116],"demonstrated":[117],"remarkable":[118],"capabilities":[119,176],"identifying":[121],"abnormalities":[123],"improving":[125,226],"quality.":[127],"Applications":[128],"include":[129],"real-time":[130],"detection":[131],"coronary":[133],"artery":[134],"stenosis":[135],"from":[136],"CT":[137],"angiography":[138],"predictive":[140],"models":[141],"events.":[144],"opaque":[147],"nature":[148],"decision":[151],"complicates":[153],"acceptance,":[155],"healthcare":[157,223],"professionals":[158],"often":[159],"lack":[160],"insight":[161],"into":[162,222],"rationale":[164],"behind":[165],"AI-generated":[166],"outputs.":[167],"Conclusion:":[168],"While":[169],"holds":[171],"promise":[172],"advancing":[174],"care,":[179],"prevailing":[181],"\"black":[182],"box\"":[183],"issue":[184],"necessitates":[185],"development":[187],"explainable":[189],"frameworks.":[191],"Enhancing":[192],"transparency":[193],"crucial":[197],"fostering":[199],"trust":[200],"among":[201],"clinicians":[202],"ensuring":[204],"implementation":[206],"settings.":[209],"Addressing":[210],"these":[211],"challenges":[212],"essential":[214],"responsible":[217],"practices,":[224],"ultimately":[225],"patient":[227],"outcomes.":[228]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-03T00:00:00"}