2025
Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management
Armoundas A, Ahmad F, Attia Z, Doudesis D, Khera R, Kyriakoulis K, Stergiou G, Tang W. Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management. Hypertension 2025, 82: 929-944. PMID: 40091745, PMCID: PMC12094096, DOI: 10.1161/hypertensionaha.124.22349.Peer-Reviewed Original ResearchConceptsArtificial intelligenceHypertension diagnosisBlood pressure elevationRelationship to cardiovascular diseaseManagement of hypertensionLong-term managementArtificial intelligence-based solutionsPressure elevationPublic health challengeHypertensionArtificial intelligence scienceComplex pathogenesisClinical implementationCardiovascular diseaseState-of-artDiagnosisData-driven approachHypertension managementIntelligence scienceClinical adoption
2024
Non-invasive preimplantation genetic testing for aneuploidy: is the promise real?
Volovsky M, Scott R, Seli E. Non-invasive preimplantation genetic testing for aneuploidy: is the promise real? Human Reproduction 2024, 39: 1899-1908. PMID: 38970367, DOI: 10.1093/humrep/deae151.Peer-Reviewed Original ResearchNon-invasive PGT-APGT-APreimplantation genetic testingIntegration of next-generation sequencingGenetic testingGenetic testing platformsNon-invasive preimplantation genetic testingNext-generation sequencingRisk of pregnancy lossAneuploidy screening methodsEmbryo culture mediumAmplification failureSegmental aneuploidyPregnancy lossCulture mediumClinical reliabilityAneuploidyDiagnostic precisionClinical settingDiagnostic inaccuracyEmbryo viabilityClinical adoptionEmbryosScreening methodDNAA large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information
Ramakrishnan D, Jekel L, Chadha S, Janas A, Moy H, Maleki N, Sala M, Kaur M, Petersen G, Merkaj S, von Reppert M, Baid U, Bakas S, Kirsch C, Davis M, Bousabarah K, Holler W, Lin M, Westerhoff M, Aneja S, Memon F, Aboian M. A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Scientific Data 2024, 11: 254. PMID: 38424079, PMCID: PMC10904366, DOI: 10.1038/s41597-024-03021-9.Peer-Reviewed Original ResearchConceptsWhole-brain radiotherapyStereotactic radiosurgeryT1 post-contrastBrain metastasesPost-contrastSide effectsImage informationArtificial intelligenceAssociated with cognitive side effectsContrast-enhancing lesionsQuality of datasetsCognitive side effectsFLAIR MR imagesValidation of AI modelsBrain radiotherapyLimitations of algorithmsStandard treatmentAI modelsMR imagingAI networksContrast enhancementClinical settingSegmentation workflowDatasetClinical adoption
2022
Randomized Clinical Trials of Machine Learning Interventions in Health Care
Plana D, Shung DL, Grimshaw AA, Saraf A, Sung JJY, Kann BH. Randomized Clinical Trials of Machine Learning Interventions in Health Care. JAMA Network Open 2022, 5: e2233946. PMID: 36173632, PMCID: PMC9523495, DOI: 10.1001/jamanetworkopen.2022.33946.Peer-Reviewed Original ResearchConceptsRandomized clinical trialsRisk of biasClinical trialsSystematic reviewNon-RCT designHealth careCONSORT-AIClinical adoptionCochrane riskOvid EmbaseCochrane LibraryTrial characteristicsOvid MEDLINEPrimary interventionExclusion criteriaCommon reasonMedian proportionPatient careRCT designLiterature searchOverall riskRelevant articlesLack of participantsTrialsGoogle ScholarPrediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer (SWOG S0800) using image analysis-based tumor infiltrating lymphocyte measurements.
Blenman K, Fanucci K, Bai Y, Pelekanou V, Nahleh Z, Shafi S, Burela S, Barlow W, Sharma P, Thompson A, Godwin A, Rimm D, Hortobagyi G, Pusztai L. Prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer (SWOG S0800) using image analysis-based tumor infiltrating lymphocyte measurements. Journal Of Clinical Oncology 2022, 40: 594-594. DOI: 10.1200/jco.2022.40.16_suppl.594.Peer-Reviewed Original ResearchPathologic complete responseBreast cancerNeoadjuvant chemotherapyComplete responseTIL scoreResidual diseaseResponse predictive markersBetter EFSBevacizumab benefitLymphocyte measurementsTIL assessmentFree survivalPredictive markerTIL quantificationInternational guidelinesPretreatment samplesLogistic regressionCancerOutcome discriminationChemotherapyScoresContinuous scoresTumorsClinical adoptionStrong positive correlation
2019
Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization
Onofrey JA, Casetti-Dinescu DI, Lauritzen AD, Sarkar S, Venkataraman R, Fan RE, Sonn GA, Sprenkle PC, Staib LH, Papademetris X. Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2019, 00: 348-351. PMID: 32874427, PMCID: PMC7457546, DOI: 10.1109/isbi.2019.8759295.Peer-Reviewed Original ResearchDeep neural networksNeural networkDeep learning algorithmsProstate gland segmentationImage normalization methodGland segmentationLearning algorithmImage normalizationMulti-site dataIntensity normalization methodNormalization methodSingle-site dataAlgorithmNetworkPotential solutionsEquipment sourcesClinical adoptionSegmentationTrainingIntensity characteristicsRobustnessDataSite trainingMethodAdoption
2013
Tissue microarrays: leaping the gap between research and clinical adoption
Gustavson MD, Rimm DL, Dolled-Filhart M. Tissue microarrays: leaping the gap between research and clinical adoption. Personalized Medicine 2013, 10: 441-451. PMID: 29758838, DOI: 10.2217/pme.13.42.Peer-Reviewed Original ResearchTissue microarrayClinical laboratory settingUse of TMAsRoutine diagnostic purposesAdvanced imagingClinical settingPatient samplesDiagnostic useTissue assessmentTranslational research settingsExpression assessmentClinical research applicationsBiomarker analysisDiagnostic assaysDiagnostic purposesResearch settingsClinical adoption
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply