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 ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceBreastBreast NeoplasmsFemaleHumansMachine LearningNeural Networks, ComputerConceptsArtificial intelligenceApplication of AIComplex artificial intelligenceDevelopment of algorithmsComputer visionDeep learningMachine learningMitosis detectionDigital pathologyNeural networkDigital dataHistology imagesTissue segmentationField of pathologyImage analysisIntelligencePromising resultsTaskLearningImagesSegmentationBreast pathologyComputerAlgorithmNetworkUsing Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma
Johannet P, Coudray N, Donnelly DM, Jour G, Illa-Bochaca I, Xia Y, Johnson DB, Wheless L, Patrinely JR, Nomikou S, Rimm DL, Pavlick AC, Weber JS, Zhong J, Tsirigos A, Osman I. Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma. Clinical Cancer Research 2021, 27: 131-140. PMID: 33208341, PMCID: PMC7785656, DOI: 10.1158/1078-0432.ccr-20-2415.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedDisease ProgressionDrug Resistance, NeoplasmFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedImmune Checkpoint InhibitorsMachine LearningMaleMelanomaMiddle AgedNeoplasm StagingPrognosisProgression-Free SurvivalProspective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsConceptsProgression-free survivalImmune checkpoint inhibitorsLower riskClinicodemographic characteristicsAdvanced melanomaClinical dataWorse progression-free survivalICI treatment outcomesKaplan-Meier curvesBiomarkers of responseStandard of careCheckpoint inhibitorsICI responseImmunotherapy responseValidation cohortTraining cohortDisease progressionProspective validationTreatment outcomesHigh riskClinical practicePatientsROC curveProgressionRisk
2018
Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
Klauschen F, Müller K, Binder A, Bockmayr M, Hägele M, Seegerer P, Wienert S, Pruneri G, de Maria S, Badve S, Michiels S, Nielsen TO, Adams S, Savas P, Symmans F, Willis S, Gruosso T, Park M, Haibe-Kains B, Gallas B, Thompson AM, Cree I, Sotiriou C, Solinas C, Preusser M, Hewitt SM, Rimm D, Viale G, Loi S, Loibl S, Salgado R, Denkert C, Group O. Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning. Seminars In Cancer Biology 2018, 52: 151-157. PMID: 29990622, DOI: 10.1016/j.semcancer.2018.07.001.Peer-Reviewed Original ResearchConceptsClassical image segmentationLearning-based approachImage analysis approachImage segmentationTraining dataConventional machineExplainable machineVisual approachPlausibility checksML resultsSegmentationMachineSuch approachesLimited precisionShape propertiesDecision-making processLarge amountScoring approachComplex propertiesAnalysis approachHeatmapsTIL quantificationObjectsBiomedical researchEstimationNuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers
Lu C, Romo-Bucheli D, Wang X, Janowczyk A, Ganesan S, Gilmore H, Rimm D, Madabhushi A. Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers. Laboratory Investigation 2018, 98: 1438-1448. PMID: 29959421, PMCID: PMC6214731, DOI: 10.1038/s41374-018-0095-7.Peer-Reviewed Original ResearchConceptsEarly-stage estrogen receptor-positive breast cancerEstrogen receptor-positive breast cancerReceptor-positive breast cancerBreast cancerRank sum testHazard ratioHistomorphometric featuresShort-term overall survivalLymph node negativeTissue microarray cohortPoor survival outcomesUnivariate survival analysisWilcoxon rank sum testAdjuvant chemotherapyMicroarray cohortOverall survivalNode negativeT stageHistology gradePatient survivalSurvival outcomesPathological parametersNuclear gradeOutcome groupPoor survival