2024
Assessing the impact of deep‐learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes
Bogaerts J, Steenbeek M, Bokhorst J, van Bommel M, Abete L, Addante F, Brinkhuis M, Chrzan A, Cordier F, Devouassoux‐Shisheboran M, Fernández‐Pérez J, Fischer A, Gilks C, Guerriero A, Jaconi M, Kleijn T, Kooreman L, Martin S, Milla J, Narducci N, Ntala C, Parkash V, de Pauw C, Rabban J, Rijstenberg L, Rottscholl R, Staebler A, Van de Vijver K, Zannoni G, van Zanten M, Bart J, Bentz J, Bosse T, Bulten J, Desouki M, Lastra R, Numan T, Schoolmeester J, Schwartz L, Shih I, Soong T, Turashvili G, Vang R, Volchek M, Aliredjo R, Kusters‐Vandevelde H, de Hullu J, Simons M, van der Laak J. Assessing the impact of deep‐learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes. The Journal Of Pathology Clinical Research 2024, 10: e70006. PMID: 39439213, PMCID: PMC11496567, DOI: 10.1002/2056-4538.70006.Peer-Reviewed Original ResearchConceptsDeep learning modelsSerous tubal intraepithelial carcinomaArtificial intelligenceAI assistanceDiagnosis of serous tubal intraepithelial carcinomaTubal intraepithelial carcinomaReview timeFallopian tubeIntraepithelial carcinomaAI supportHigh-grade serous ovarian carcinomaSerous ovarian carcinomaStandalone performanceAverage sensitivityGroup of pathologistsAccuracyOvarian carcinomaHistopathological diagnosisPathologist performanceMixed-model analysisDiagnostic certaintyCarcinomaDiagnostic setting
2020
Deep learning assistance for the histopathologic diagnosis of Helicobacter pylori
Zhou S, Marklund H, Blaha O, Desai M, Martin B, Bingham D, Berry G, Gomulia E, Ng A, Shen J. Deep learning assistance for the histopathologic diagnosis of Helicobacter pylori. Intelligence-Based Medicine 2020, 1: 100004. DOI: 10.1016/j.ibmed.2020.100004.Peer-Reviewed Original Research
2019
Validation of mitotic cell quantification via microscopy and multiple whole-slide scanners
Tabata K, Uraoka N, Benhamida J, Hanna M, Sirintrapun S, Gallas B, Gong Q, Aly R, Emoto K, Matsuda K, Hameed M, Klimstra D, Yagi Y. Validation of mitotic cell quantification via microscopy and multiple whole-slide scanners. Diagnostic Pathology 2019, 14: 65. PMID: 31238983, PMCID: PMC6593538, DOI: 10.1186/s13000-019-0839-8.Peer-Reviewed Original ResearchConceptsIntra-observer agreementMitotic figuresEvaluate mitotic activityCanine oral melanomaWhole-slide imagesEye examinationOral melanomaNaked eye examinationDetectable mitotic figuresMitotic activityConsensus panelWhole-slide imaging scannersCohen's kappaCell quantificationPathologistsConclusionsThis studyPathologist performanceMitotic figure detectionAverage of sensitivityAutomatic quantification
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