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Sebastian Haferkamp (1978-)

Name	Sebastian Haferkamp
Zeit	1978- (Lebensdaten)
Ort	Essen (Geburtsort) Deutschland
Geschlecht	männlich
Akademischer Grad bzw. Titel	Dr. med.
Beziehung	Universitätsklinikum Regensburg
Weitere Angaben	Habil.-Schr. im Fach Dermatologie und Venerologie der Medizinischen Fakultät der Universität Würzburg, 2014;
Quelle	Vorlage, WWW: http://www.ukr.de/kliniken-institute/Dermatologie/Klinikteam___Mitarbeiter/__rztlicher_dienst/Ober__rztInnen/ (Stand: 16.11.2016)
Datensatztyp	Person
GND-Nummer	132018330
Datensatz-ID	132018330
Beteiligt an alle anzeigen Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark Model soups improve performance of dermoscopic skin cancer classifiers Incidence and Mortality of Malignant Melanoma in Relation to Dermatologist Density in Bavaria A benchmark for neural network robustness in skin cancer classification Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study Incidence and Mortality of Malignant Melanoma in Relation to Dermatologist Density in Bavaria Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks : Systematic Review Patterns of care and follow-up care of patients with uveal melanoma in German-speaking countries: a multinational survey of the German Dermatologic Cooperative Oncology Group (DeCOG) Patients with BRAF-Mutant Advanced/Metastatic Melanoma: Original Research on the Treatment Reality in Germany and Austria in the Era of Choice Combined immunotherapy with nivolumab and ipilimumab with and without local therapy in patients with melanoma brain metastasis: a DeCOG* study in 380 patients Effects of Label Noise on Deep Learning-Based Skin Cancer Classification Patterns of care and follow-up care of patients with uveal melanoma in German-speaking countries: a multinational survey of the German Dermatologic Cooperative Oncology Group (DeCOG) Zelluläre Seneszenz ؛n der Entwicklung und Therapie des malignen Melanoms Charakterisierung der Glykoproteine des hämorrhagischen Krim-Kongo-Fieber-Virus

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Katalog der Deutschen Nationalbibliothek

Sebastian Haferkamp (1978-)

Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark

Model soups improve performance of dermoscopic skin cancer classifiers

Incidence and Mortality of Malignant Melanoma in Relation to Dermatologist Density in Bavaria

A benchmark for neural network robustness in skin cancer classification

Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification

Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study

Incidence and Mortality of Malignant Melanoma in Relation to Dermatologist Density in Bavaria

Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks : Systematic Review

Patterns of care and follow-up care of patients with uveal melanoma in German-speaking countries: a multinational survey of the German Dermatologic Cooperative Oncology Group (DeCOG)

Patients with BRAF-Mutant Advanced/Metastatic Melanoma: Original Research on the Treatment Reality in Germany and Austria in the Era of Choice

Combined immunotherapy with nivolumab and ipilimumab with and without local therapy in patients with melanoma brain metastasis: a DeCOG* study in 380 patients

Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

Patterns of care and follow-up care of patients with uveal melanoma in German-speaking countries: a multinational survey of the German Dermatologic Cooperative Oncology Group (DeCOG)

Zelluläre Seneszenz ؛n der Entwicklung und Therapie des malignen Melanoms

Charakterisierung der Glykoproteine des hämorrhagischen Krim-Kongo-Fieber-Virus