2024
A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey
Vahdati S, Khosravi B, Mahmoudi E, Zhang K, Rouzrokh P, Faghani S, Moassefi M, Tahmasebi A, Andriole K, Chang P, Farahani K, Flores M, Folio L, Houshmand S, Giger M, Gichoya J, Erickson B. A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey. Journal Of Imaging Informatics In Medicine 2024, 37: 2015-2024. PMID: 38558368, PMCID: PMC11522208, DOI: 10.1007/s10278-024-01083-0.Peer-Reviewed Original ResearchConceptsArtificial intelligenceData curationSuccess of machine learningMedical image dataArtificial intelligence applicationsAI model developmentOpen-source toolIntelligence applicationsAI applicationsImaging informaticsMachine learningMedical imagesAI modelsOpen-sourceData readinessData preparationImage dataAnalytics projectsResearch areaArtificialDataCurationDecision-making processCompilation of toolsImages
2022
QOPI Clinical Informatics: A digital platform to enable real-time quality reporting, clinical decision support, and rapid learning.
Williams C, Karagoz K, Elsey R, Meißner T, Higashi M, Schadt E, Jun T, Wang X, Chen R, Zhou X, Guin S, Lee J, Oh W. QOPI Clinical Informatics: A digital platform to enable real-time quality reporting, clinical decision support, and rapid learning. Journal Of Clinical Oncology 2022, 40: e13545-e13545. DOI: 10.1200/jco.2022.40.16_suppl.e13545.Peer-Reviewed Original ResearchQuality Oncology Practice InitiativeClinical decision supportDecision supportData visualization techniquesCancer careClinical Oncology Quality Oncology Practice InitiativeASCO's Quality Oncology Practice InitiativeTemporal reasoningPractice initiativesBreast cancer patientsInteractive graphsTumor molecular profilingVisual platformData curationNLP methodsMolecular tumor boardPatient referral patternsAmerican SocietyVisualization techniquesContinuous learning environmentData captureClinical informaticsRapid learningDigital platformsQuality reporting
2020
Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations
Comess S, Akbay A, Vasiliou M, Hines RN, Joppa L, Vasiliou V, Kleinstreuer N. Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations. Frontiers In Artificial Intelligence 2020, 3: 31. PMID: 33184612, PMCID: PMC7654840, DOI: 10.3389/frai.2020.00031.Peer-Reviewed Original ResearchBig dataArtificial InteligenceSkilled data scientistsComplex data setsData scientistsScientific computingCyber infrastructureMachine learningAI approachesReusable dataFAIR principlesData curationComputational toolsData setsEnvironmental public health researchResearch hubData collectionActionable recommendationsBroader public health communityComputingSharingInteligenceSufficient informationCurationParamount importance
2019
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Campanella G, Hanna M, Geneslaw L, Miraflor A, Werneck Krauss Silva V, Busam K, Brogi E, Reuter V, Klimstra D, Fuchs T. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nature Medicine 2019, 25: 1301-1309. PMID: 31308507, PMCID: PMC7418463, DOI: 10.1038/s41591-019-0508-1.Peer-Reviewed Original ResearchConceptsDecision support systemWhole slide imagesTrain accurate classification modelsManually annotated datasetDevelopment of decision support systemsSlide imagesPixel-wise manual annotationSupervised deep learningSupport systemAccurate classification modelDeep learning systemComputer decision support systemDeep learningManual annotationData curationClassification modelLearning systemComputational pathologyDatasetDeploymentMetastasis to axillary lymph nodesAxillary lymph nodesBasal cell carcinomaClinical practiceImages
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