2024
Release of complex imaging reports to patients, do radiologists trust AI to help?
Amin K, Davis M, Naderi A, Forman H. Release of complex imaging reports to patients, do radiologists trust AI to help? Current Problems In Diagnostic Radiology 2024, 54: 147-150. PMID: 39676024, DOI: 10.1067/j.cpradiol.2024.12.008.Peer-Reviewed Original ResearchRadiology reportsArtificial intelligenceImprove patient comprehensionAcademic medical centerEight-question surveyManual checkingPatient portalsCentury Cures ActArtificial intelligence systemsArtificial intelligence technologyPatient comprehensionOpinions of radiologistsClinical fellowsIntelligent systemsCures ActMedical CenterImaging ReportingIntelligence technologyRadiology attendingsContact informationPatientsRadiologistsRadiologyDesigning medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility
Oikonomou E, Khera R. Designing medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility. Hellenic Journal Of Cardiology 2024, 81: 9-17. PMID: 39025234, DOI: 10.1016/j.hjc.2024.07.003.Peer-Reviewed Original ResearchArtificial intelligenceMedical artificial intelligence systemsDesigning AI systemsMachine learning systemsArtificial intelligence systemsBenefits of AIIntelligent systemsAI systemsLearning systemEnd-usersData typesAI developmentInteroperabilityTemporal settingAccessScalabilityTreatment of cardiovascular diseasesIntelligenceSystemMachineQuality assuranceInternational cohortCardiovascular diseaseObstacles407 IMPACT OF ARTIFICIAL INTELLIGENCE SYSTEMS FOR UPPER GASTROINTESTINAL BLEEDING ON CLINICIAN TRUST AND LEARNING USING LARGE LANGUAGE MODELS: A RANDOMIZED PILOT SIMULATION STUDY
Chung S, Rajashekar N, Pu Y, Shin Y, Giuffrè M, Chan C, You K, Saarinen T, Hsiao A, Sekhon J, Wong A, Evans L, McCall T, Kizilcec R, Laine L, Shung D. 407 IMPACT OF ARTIFICIAL INTELLIGENCE SYSTEMS FOR UPPER GASTROINTESTINAL BLEEDING ON CLINICIAN TRUST AND LEARNING USING LARGE LANGUAGE MODELS: A RANDOMIZED PILOT SIMULATION STUDY. Gastroenterology 2024, 166: s-95-s-96. DOI: 10.1016/s0016-5085(24)00715-7.Peer-Reviewed Original ResearchArtificial intelligence systemsLanguage modelIntelligent systemsSimulation studyPilot simulation study
2023
Integration of Cyber-Physical Systems in the Advancement of Society 5.0 Healthcare Management
Damane B, Kgokolo M, Gaudji G, Blenman K, Dlamini Z. Integration of Cyber-Physical Systems in the Advancement of Society 5.0 Healthcare Management. 2023, 201-221. DOI: 10.1007/978-3-031-36461-7_9.Peer-Reviewed Original ResearchCyber-physical systemsSelf-sovereign identityArtificial intelligence systemsHealthcare management systemLarge data setsOpen AuthorizationAccurate medical diagnosisSecurity layerSociety 5.0AI systemsIntelligence systemsComputational platformWrong handsPrecise tasksManagement systemDigital platformsInput dataReal-time monitoringMedical diagnosisAutomatic actuationData setsPhysical systemsCertain informationHealthcare managementPhysical elements
2020
Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies
Raciti P, Sue J, Ceballos R, Godrich R, Kunz J, Kapur S, Reuter V, Grady L, Kanan C, Klimstra D, Fuchs T. Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies. Modern Pathology 2020, 33: 2058-2066. PMID: 32393768, PMCID: PMC9235852, DOI: 10.1038/s41379-020-0551-y.Peer-Reviewed Original ResearchConceptsWhole slide imagesProstate needle core biopsiesArtificial intelligence systemsNeedle core biopsyIntelligent systemsCore biopsyProstate cancerState-of-the-artDetection of prostate cancerMachine learning algorithmsCore needle biopsyHigh test accuracyLow grade tumorsWell-differentiated cancersStained with hematoxylin and eosinAverage sensitivityLearning algorithmsHematoxylin and eosinGenitourinary pathologistsGrade tumorsNeedle biopsyDetection systemPathological diagnosisStatistically significant changesAncillary studies
2019
Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence
Ye W, Gu W, Guo X, Yi P, Meng Y, Han F, Yu L, Chen Y, Zhang G, Wang X. Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence. BioMedical Engineering OnLine 2019, 18: 6. PMID: 30670024, PMCID: PMC6343356, DOI: 10.1186/s12938-019-0627-4.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsDatabases, FactualDeep LearningDiagnosis, Computer-AssistedFalse Positive ReactionsHumansImage Processing, Computer-AssistedLungLung NeoplasmsRadiographic Image Interpretation, Computer-AssistedRadiologyReproducibility of ResultsSensitivity and SpecificitySolitary Pulmonary NoduleTomography, X-Ray ComputedConceptsDeep learningF-scoreLung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) databaseMethod of deep learningArtificial intelligence systemsInput imageNetwork trainingDetect pulmonary nodulesIdentification of lung nodulesIntelligent systemsNodule classificationGround-glass opacity imagesPreprocessing methodsDetect ground-glass opacitiesEvaluation resultsLearningAccuracyAlexNetResNet50PreprocessingImagesThree-dimensional featuresGround-glass opacitiesNetworkFeatures
2007
Fine‐needle aspiration of follicular adenoma versus parathyroid adenoma
Mansoor I, Zalles C, Zahid F, Gossage K, Levenson RM, Rimm DL. Fine‐needle aspiration of follicular adenoma versus parathyroid adenoma. Cancer 2007, 114: 22-26. PMID: 18085636, DOI: 10.1002/cncr.23252.Peer-Reviewed Original ResearchConceptsArtificial intelligence systemsSpatial-spectral featuresSpectral image informationMultispectral image analysisIntelligence systemsImage informationAlgorithmic solutionTraining setImage stacksImaging solutionImage analysisTest casesHuman eyeImagesClassifierSoftwareToolPlatformSolutionTechnologyInformationSet
1998
Alternative Essences of Intelligence
Brooks R, Breazeal C, Irie R, Kemp C, Marjanovic M, Scassellati B, Williamson M. Alternative Essences of Intelligence. 1998 DOI: 10.21236/ada457180.Peer-Reviewed Original Research
1987
Choice and Explanation in Medical Management
Rennels G, Shortliffe E, Miller P. Choice and Explanation in Medical Management. Medical Decision Making 1987, 7: 22-31. PMID: 3807687, DOI: 10.1177/0272989x8700700107.Peer-Reviewed Original Research
1986
The evaluation of artificial intelligence systems in medicine
Miller P. The evaluation of artificial intelligence systems in medicine. Computer Methods And Programs In Biomedicine 1986, 22: 3-11. PMID: 3516560, DOI: 10.1016/0169-2607(86)90087-8.Peer-Reviewed Original ResearchConceptsArtificial intelligenceArtificial intelligence systemsIntelligence systemsComputer systemsSystem knowledgeOperational systemResearch contributionsEvaluation issuesIntelligenceDevelopmental prototypeSubjective evaluationSystemPrototypeDifferent levelsIssuesFrameworkKnowledgeEvaluationPerformance
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