2024
Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders
Rahaman A, Garg Y, Iraji A, Fu Z, Kochunov P, Hong L, Van Erp T, Preda A, Chen J, Calhoun V. Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders. Human Brain Mapping 2024, 45: e26799. PMID: 39562310, PMCID: PMC11576332, DOI: 10.1002/hbm.26799.Peer-Reviewed Original ResearchConceptsNeural networkDilated convolutional neural networkJoint learning frameworkAttention scoresState-of-the-artDeep neural networksNeural network decisionsConvolutional neural networkAttention fusionFusion moduleDiverse data sourcesArtificial intelligence modelsLearning frameworkAttention moduleJoint learningMultimodal clusteringNetwork decisionsInput streamMultimodal learningHigh-dimensionalIntermediate fusionFused dataSZ classificationIntelligence modelsContextual patternsChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation
Kyro G, Morgunov A, Brent R, Batista V. ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation. Journal Of Chemical Information And Modeling 2024, 64: 653-665. PMID: 38287889, DOI: 10.1021/acs.jcim.3c01456.Peer-Reviewed Original ResearchConceptsVastness of chemical spaceMolecular generationDomain of drug discoveryArtificial intelligence modelsChemical spaceIntelligence modelsLearning methodologyPython packageDrug discoverySmall molecule inhibitorsActive learning methodologiesFDA-approved small molecule inhibitorsMoleculesEfficient methodDomainSoftwareC-Abl kinaseReproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
Elfer K, Gardecki E, Garcia V, Ly A, Hytopoulos E, Wen S, Hanna M, Peeters D, Saltz J, Ehinger A, Dudgeon S, Li X, Blenman K, Chen W, Green U, Birmingham R, Pan T, Lennerz J, Salgado R, Gallas B. Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models. Modern Pathology 2024, 37: 100439. PMID: 38286221, DOI: 10.1016/j.modpat.2024.100439.Peer-Reviewed Original ResearchArtificial intelligenceAnnotation of medical imagesMedical imagesTesting artificial intelligenceTest data setsArtificial intelligence modelsAnnotation effortEvaluative annotationsDiagnostic image analysisIntelligence modelsAnnotation workflowData setsDigital pathologyAnnotationQuality frameworkIntelligenceArtificialWorkflowImage analysisPrediction modelMetadataConsolidated Standards of Reporting TrialsFrameworkImagesStandards for Reporting Diagnostic Accuracy
2023
ChemSpaceAL: An efficient active learning methodology applied to protein-specific molecular generation
Kyro G, Morgunov A, Brent R, Batista V. ChemSpaceAL: An efficient active learning methodology applied to protein-specific molecular generation. Biophysical Journal 2023, 123: 283a. PMID: 37744464, PMCID: PMC10516108, DOI: 10.1016/j.bpj.2023.11.1763.Peer-Reviewed Original ResearchMolecular generationVastness of chemical spaceLearning methodologyActive learning methodologiesDomain of drug discoveryArtificial intelligence modelsChemical spaceGenerative modelIntelligence modelsPython packageDrug discoverySample spaceSmall molecule inhibitorsFDA-approved small molecule inhibitorsMoleculesEfficient methodDomainSoftwareApplicationsMethodologyC-Abl kinaseImplementationSpaceMethodDetection of Large-Droplet Macrovesicular Steatosis in Donor Livers Based on Segment-Anything Model
Tang H, Jiao J, Lin J, Zhang X, Sun N. Detection of Large-Droplet Macrovesicular Steatosis in Donor Livers Based on Segment-Anything Model. Laboratory Investigation 2023, 104: 100288. PMID: 37977550, DOI: 10.1016/j.labinv.2023.100288.Peer-Reviewed Original ResearchLiver diseaseMacrovesicular steatosisArtificial intelligence algorithmsArtificial intelligence modelsEnd-stage liver diseaseRule-based algorithmLiver histology analysisLiver transplant complicationsAcute liver failurePrimary hepatic malignancyLarge fat vacuolesIntelligence algorithmsDetection modelTransformer architectureIntelligence modelsTransplant complicationsLiver transplantationLiver failureLiver biopsyHepatic malignanciesFat vacuolesDonor organsEffective treatmentPrior knowledgeAlgorithmFoundation models for generalist medical artificial intelligence
Moor M, Banerjee O, Abad Z, Krumholz H, Leskovec J, Topol E, Rajpurkar P. Foundation models for generalist medical artificial intelligence. Nature 2023, 616: 259-265. PMID: 37045921, DOI: 10.1038/s41586-023-05881-4.Peer-Reviewed Original ResearchConceptsMedical AILarge medical datasetsMedical artificial intelligenceArtificial intelligence modelsImage annotationMedical datasetsArtificial intelligenceElectronic health recordsAI devicesIntelligence modelsTraining datasetDiverse datasetsExpressive outputHealth recordsRapid developmentDatasetFree-text explanationsMedical modalitiesNew paradigmMedical textsAITechnical capabilitiesDiverse setNewfound capabilitiesCapability
2022
Mitigating Bias in Radiology Machine Learning: 3. Performance Metrics
Faghani S, Khosravi B, Zhang K, Moassefi M, Jagtap J, Nugen F, Vahdati S, Kuanar S, Rassoulinejad-Mousavi S, Singh Y, Vera Garcia D, Rouzrokh P, Erickson B. Mitigating Bias in Radiology Machine Learning: 3. Performance Metrics. Radiology Artificial Intelligence 2022, 4: e220061. PMID: 36204539, PMCID: PMC9530766, DOI: 10.1148/ryai.220061.Peer-Reviewed Original Research
2021
Artificial Intelligence-Based Image Enhancement in PET Imaging Noise Reduction and Resolution Enhancement
Liu J, Malekzadeh M, Mirian N, Song TA, Liu C, Dutta J. Artificial Intelligence-Based Image Enhancement in PET Imaging Noise Reduction and Resolution Enhancement. PET Clinics 2021, 16: 553-576. PMID: 34537130, PMCID: PMC8457531, DOI: 10.1016/j.cpet.2021.06.005.Peer-Reviewed Original ResearchConceptsArtificial intelligence modelsImage enhancementIntelligence modelsArtificial intelligenceNetwork architectureEvaluation metricsLarge-scale adoptionData typesImage denoisingLoss functionPET imagesLow spatial resolutionHigh noiseResolution enhancementImagesIntelligenceDeblurringArchitectureDenoisingNoise reductionMetricsPopularityRecent effortsFuture directionsAccuracyDeep Learning Artificial Intelligence Model for Assessment of Hip Dislocation Risk Following Primary Total Hip Arthroplasty From Postoperative Radiographs
Rouzrokh P, Ramazanian T, Wyles C, Philbrick K, Cai J, Taunton M, Maradit Kremers H, Lewallen D, Erickson B. Deep Learning Artificial Intelligence Model for Assessment of Hip Dislocation Risk Following Primary Total Hip Arthroplasty From Postoperative Radiographs. The Journal Of Arthroplasty 2021, 36: 2197-2203.e3. PMID: 33663890, PMCID: PMC8154724, DOI: 10.1016/j.arth.2021.02.028.Peer-Reviewed Original Research
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