Self-supervised learning in histopathology: New perspectives for prostate cancer grading. Lecture Notes in Computer Science, 348--360, Springer Nature Switzerland, Cham, 2024. [PUMA: Yaff cancer grading histopathology learning prostate self-supervised topic_lifescience]
An ensemble approach for histopathological classification of vulvar cancer. In John E Tomaszewski, und Aaron D Ward (Hrsg.), Medical Imaging 2023: Digital and Computational Pathology, 40, SPIE, April 2023. [PUMA: approach cancer classification ensemble histopathological nopdf vulvar]
Secondary Treatment for Men with Localized Prostate Cancer: A Pooled Analysis of PRIAS and ERSPC-Rotterdam Data within the PIONEER Data Platform. Journal of Personalized Medicine, (12)5:751, MDPI AG, Mai 2022. [PUMA: Cancer ERSPC-Rotterdam Localized Men PIONEER PRIAS Prostate Secondary Treatment Zno] URL
Generation of a Realistic Synthetic Laryngeal Cancer Cohort for AI Applications. Cancers, (16)3:639, MDPI AG, Februar 2024. [PUMA: AI Applications Cancer Cohort Generation Laryngeal Realistic Synthetic zno] URL
A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer. Molecular Medicine, (30)1Springer Science and Business Media LLC, Februar 2024. [PUMA: Yaff applicable biopsies cancer formalin-fixed paraffin-embedded predictionprostate risk-score transcriptomic] URL
An Open-Source Approach for Digital Prostate Cancer Histopathology: Bringing AI into Practice. Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS, 729-738, SciTePress, 2024. [PUMA: AI Cancer Digital Histopatholog Open-Source Prostate nopdf]
Predicting mutational status of driver and suppressor genes directly from histopathology with Deep Learning: A systematic study across 23 solid tumor types. Front. Genet., (12):806386, 2021. [PUMA: (AI); TCGA; artificail cancer deep genes; genetic intelligence learning; pathway pathway;]
Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images. Cancers (Basel), (15)7April 2023. [PUMA: topic_lifescience cancer cancer; classification; colorectal convolutional filter; hyperspectral imaging; learning; machine median networks; post-processing; pre-processing]