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Prof. Schüffler's (*1983) field of research is the area of digital and computational pathology. This includes novel machine learning approaches for the detection, segmentation and grading of cancer in pathology images, prediction of prognostic markers and outcome prediction (e.g. treatment response). Further, he investigates the efficient visualization of high-resolution digital pathology images, automated QA, new ergonomics for pathologists, and holistic integration of digital systems for clinics, research and education.
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论文共 77 篇作者统计合作学者相似作者
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Tobias Lahmer,Gregor Weirich,Stefan Porubsky,Sebastian Rasch, Florian A. Kammerstetter, Christian Schustetter,Peter Schueffler,Johanna Erber,Miriam Dibos,Claire Delbridge,Peer Hendrik Kuhn,Samuel Jeske,
DIAGNOSTICSno. 3 (2024): 294
Viola Iwuajoku,Anette Haas, Kübra Ekici, Mohammad Zaid Khan,Fabian Stögbauer,Katja Steiger,Carolin Mogler,Peter J. Schüffler
Die Pathologieno. 2 (2024): 98-105
Viola Iwuajoku,Anette Haas, Kübra Ekici, Mohammad Zaid Khan,Fabian Stögbauer,Katja Steiger,Carolin Mogler,Peter J Schüffler
Pathologie (Heidelberg, Germany)no. 2 (2024): 98-105
Pathologie (Heidelberg, Germany) (2024)
Die Pathologiepp.1-5, (2024)
MACHINE LEARNING IN MEDICAL IMAGING, MLMI 2023, PT II (2024): 427-436
GENES CHROMOSOMES & CANCERno. 9 (2023): 564-567
Patricia Raciti,Jillian Sue, Juan A. Retamero,Rodrigo Ceballos,Ran Godrich,Jeremy D. Kunz,Adam Casson, Dilip Thiagarajan, Zahra Ebrahimzadeh,Julian Viret,Donghun Lee,Peter J. Schuffler,
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINEno. 10 (2023): 1178-1185
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