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Author Details

Christof von Kalle
Berlin Institute of Health at Charite-Universitatsmedizin Berlin
1990
280
81
PMIDPaper TitleJournal TitlePublished Year
37434025Analysis of acute COVID-19 including chronic morbidity: protocol for the deep phenotyping National Pandemic Cohort Network in Germany (NAPKON-HAP).Infection2024
36572146Cenicriviroc for the treatment of COVID-19: first interim results of a randomised, placebo-controlled, investigator-initiated, double-blind phase II trial.J Glob Antimicrob Resist2023
37490312Interoperable, Domain-Specific Extensions for the German Corona Consensus (GECCO) COVID-19 Research Data Set Using an Interdisciplinary, Consensus-Based Workflow: Data Set Development Study.JMIR Med Inform2023
37690178A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology.Eur J Cancer2023
37382622A self-supervised vision transformer to predict survival from histopathology in renal cell carcinoma.World J Urol2023
35976907Deep learning can predict survival directly from histology in clear cell renal cell carcinoma.PLoS One2022
35390650Explainable artificial intelligence in skin cancer recognition: A systematic review.Eur J Cancer2022
36480778Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care.JCO Precis Oncol2022
35973360Model soups improve performance of dermoscopic skin cancer classifiers.Eur J Cancer2022
35904671The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics.Eur J Epidemiol2022
35916701Uncertainty Estimation in Medical Image Classification: Systematic Review.JMIR Med Inform2022
32949162Integrating proteomics into precision oncology.Int J Cancer2021
33602930Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients.Nat Commun2021
33675648Renewed Absence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infections in the Day Care Context in Berlin, January 2021.Clin Infect Dis2021
33706408Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer.BJU Int2021
33838393Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification.Eur J Cancer2021
33528370Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study.J Med Internet Res2021
34642875Long-term health sequelae and quality of life at least 6 months after infection with SARS-CoV-2: design and rationale of the COVIDOM-study as part of the NAPKON population-based cohort platform (POP).Infection2021
34785797Publisher Correction: Comprehensive genomic characterization of gene therapy-induced T-cell acute lymphoblastic leukemia.Leukemia2021
34391053Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review.Eur J Cancer2021
34509059Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.Eur J Cancer2021
34388516A benchmark for neural network robustness in skin cancer classification.Eur J Cancer2021
34448448SARS-CoV-2 infection and transmission in school settings during the second COVID-19 wave: a cross-sectional study, Berlin, Germany, November 2020.Euro Surveill2021
34649117Deep learning can predict lymph node status directly from histology in colorectal cancer.Eur J Cancer2021
34102097Delayed Antibody and T-Cell Response to BNT162b2 Vaccination in the Elderly, Germany.Emerg Infect Dis2021
34298373Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.Eur J Cancer2021
33956945SARS-CoV-2 infections in kindergartens and associated households at the start of the second wave in Berlin, Germany-a cross-sectional study.Eur J Public Health2021
34141871MicroRNA-sensitive oncolytic measles virus for chemovirotherapy of pancreatic cancer.Mol Ther Oncolytics2021
34112699Comprehensive Genomic and Transcriptomic Analysis for Guiding Therapeutic Decisions in Patients with Rare Cancers.Cancer Discov2021
34086232Deutschland krempelt die ÿrmel hoch.MMW Fortschr Med2021
34021250The balance between the intronic miR-342 and its host gene Evl determines hematopoietic cell fate decision.Leukemia2021
33423009Robustness of convolutional neural networks in recognition of pigmented skin lesions.Eur J Cancer2021
31558800Identification and characterization of a BRAF fusion oncoprotein with retained autoinhibitory domains.Oncogene2020
32053093Sequencing of serially passaged measles virus affirms its genomic stability and reveals a nonrandom distribution of consensus mutations.J Gen Virol2020
32008919Reply to the letter to the editor: 'Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images'.Eur J Cancer2020
33251725ÿberdiagnose von Melanomen - Ursachen, Konsequenzen und Lösungsansätze.J Dtsch Dermatol Ges2020
33349259The German Corona Consensus Dataset (GECCO): a standardized dataset for COVID-19 research in university medicine and beyond.BMC Med Inform Decis Mak2020
32915161Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.J Med Internet Res2020
32591762COVID-19 severity correlates with airway epithelium-immune cell interactions identified by single-cell analysis.Nat Biotechnol2020
32619549Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection.Cell Syst2020
32728813[External scientific evaluation of the first teledermatology app without direct patient contact in Germany (Online Dermatologist-AppDoc)].Hautarzt2020
32841508Overdiagnosis of melanoma - causes, consequences and solutions.J Dtsch Dermatol Ges2020
32535877Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19).Infection2020
32127638Comprehensive genomic characterization of gene therapy-induced T-cell acute lymphoblastic leukemia.Leukemia2020
29028876Systematic comparative study of computational methods for T-cell receptor sequencing data analysis.Brief Bioinform2019
31708276Corrigendum to 'Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data' [Eur J Cancer, 119 (September 2019) Pages 30-34].Eur J Cancer2019
31325876Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.Eur J Cancer2019
31233565Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions.PLoS One2019
31401471Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.Eur J Cancer2019
31401469Deep neural networks are superior to dermatologists in melanoma image classification.Eur J Cancer2019
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Collaborators

German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT)
Co-authored papers 43
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Co-authored papers 25
Co-authored papers 20
National Center for Tumor Diseases (NCT) Heidelberg
Co-authored papers 18
Vita-Salute San Raffaele University
Co-authored papers 16
Co-authored papers 16
Berlin Institute of Health (BIH) and Charite
Co-authored papers 14
Institute of Pathology, University Hospital Heidelberg
Co-authored papers 11
German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT)
Co-authored papers 10
National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ)
Co-authored papers 10
University of Augsburg
Co-authored papers 8
Kinderklinik und Kinderpoliklinik der Ludwig-Maximilians-Universitat Munchen
Co-authored papers 7
Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM)
Co-authored papers 7
German Cancer Research Center (DKFZ)
Co-authored papers 7
Co-authored papers 7
German Cancer Research Center (DKFZ)
Co-authored papers 7
Institute of Pathology, University Hospital Heidelberg
Co-authored papers 6
Hopp Children's Cancer Center Heidelberg (KiTZ)
Co-authored papers 6
German Cancer Research Center (DKFZ)
Co-authored papers 6
European Bioinformatics Institute (EMBL-EBI)
Co-authored papers 6
Max Planck Institute for Molecular Genetics
Co-authored papers 6
Max Planck Institute for Molecular Genetics
Co-authored papers 6
Institute of Pathology, University Hospital Heidelberg
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St Jude Children's Research Hospital
Co-authored papers 5
N.N. Burdenko Neurosurgical Institute
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Hopp Children's Cancer Center Heidelberg (KiTZ)
Co-authored papers 5
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Hopp Children's Cancer Center Heidelberg (KiTZ)
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Hopp Children's Cancer Center (KiTZ)
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