2021
Artificial intelligence applied to breast pathology
Yousif M, van Diest PJ, Laurinavicius A, Rimm D, van der Laak J, Madabhushi A, Schnitt S, Pantanowitz L. Artificial intelligence applied to breast pathology. Virchows Archiv 2021, 480: 191-209. PMID: 34791536, DOI: 10.1007/s00428-021-03213-3.Peer-Reviewed Original ResearchConceptsArtificial intelligenceApplication of AIComplex artificial intelligenceDevelopment of algorithmsComputer visionDeep learningMachine learningMitosis detectionDigital pathologyNeural networkDigital dataHistology imagesTissue segmentationField of pathologyImage analysisIntelligencePromising resultsTaskLearningImagesSegmentationBreast pathologyComputerAlgorithmNetworkBiomarker Discovery in Patients with Immunotherapy-Treated Melanoma with Imaging Mass CytometryMultiplex Discovery with Imaging Mass Cytometry
Martinez-Morilla S, Villarroel-Espindola F, Wong PF, Toki MI, Aung TN, Pelekanou V, Bourke-Martin B, Schalper KA, Kluger HM, Rimm DL. Biomarker Discovery in Patients with Immunotherapy-Treated Melanoma with Imaging Mass CytometryMultiplex Discovery with Imaging Mass Cytometry. Clinical Cancer Research 2021, 27: 1987-1996. PMID: 33504554, PMCID: PMC8026677, DOI: 10.1158/1078-0432.ccr-20-3340.Peer-Reviewed Original Research
2020
Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images
Noorbakhsh J, Farahmand S, Foroughi pour A, Namburi S, Caruana D, Rimm D, Soltanieh-ha M, Zarringhalam K, Chuang JH. Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images. Nature Communications 2020, 11: 6367. PMID: 33311458, PMCID: PMC7733499, DOI: 10.1038/s41467-020-20030-5.Peer-Reviewed Original ResearchConceptsConvolutional neural networkWhole slide imagesPower of CNNsNormal convolutional neural networkImage data miningColon cancer imagesData miningCNN accuracyCancer imagesNeural networkHistopathological imagesManual inspectionSlide imagesData typesClassifier comparisonSignificant accuracyHistological imagesImage analysisSpatial similarityImagesClassifier pairsClassificationMutation classificationAccuracyMining
2009
Preliminary Comparison between AQUA and Centralised ER/PgR Analysis within the TEAM Pathology Study.
Bartlett J, Rimm D, Brookes C, Dolled-Filhart M, Robson T, van de Velde C, Billingham L, Campbell F, Hasenburg A, Hille E, Kieback D, Putter H, Markopoulos C, Christiansen J, Gustavson M, Mallon E, Meershoek-Klein Kranenburg E, Parideans R, Seynaeve C, Rea D. Preliminary Comparison between AQUA and Centralised ER/PgR Analysis within the TEAM Pathology Study. Cancer Research 2009, 69: 3045-3045. DOI: 10.1158/0008-5472.sabcs-09-3045.Peer-Reviewed Original ResearchER/PgRER expressionImmunohistochemical assaysAQUA scoreExemestane Adjuvant Multinational (TEAM) trialHigh ER expressionTeam patientsPatient prognosisAromatase inhibitorsMultinational trialOutcome dataPathology studiesCancer ResAQUA technologyIHCPreliminary dataPatientsRegression analysisPGR analysisFurther dataPgRImage analysisIncremental increaseScoresMultiple cores
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