Showing results (321-330 of 859) with videos related to
Sort By:
Pageof 86
Journal of Pathology Informatics|May 14, 2023
Classification of fungal genera from microscopic images using artificial intelligenceMd Arafatur Rahman, Madelyn Clinch, Jordan Reynolds, et al.Journal of Pathology Informatics|April 7, 2023
Investigation of semi- and self-supervised learning methods in the histopathological domainBenjamin Voigt, Oliver Fischer, Bruno Schilling, et al.Journal of Pathology Informatics|November 29, 2023
Handling DNA malfunctions by unsupervised machine learning modelMutaz Kh Khazaaleh, Mohammad A Alsharaiah, Wafa Alsharafat, et al.Journal of Pathology Informatics|January 18, 2024
Artificial intelligence for human gunshot wound classificationJerome Cheng, Carl Schmidt, Allecia Wilson, et al.Journal of Pathology Informatics|January 8, 2024
Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stromaLiam Burrows, Declan Sculthorpe, Hongrun Zhang, et al.Journal of Pathology Informatics|December 27, 2023
A deep learning model to predict Ki-67 positivity in oral squamous cell carcinomaFrancesco Martino, Gennaro Ilardi, Silvia Varricchio, et al.Journal of Pathology Informatics|December 13, 2023
Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic reviewRicardo Gonzalez, Peyman Nejat, Ashirbani Saha, et al.Journal of Pathology Informatics|December 21, 2023
Comparative evaluation of slide scanners, scan settings, and cytopreparations for digital urine cytologyJen-Fan Hang, Yen-Chuan Ou, Wei-Lei Yang, et al.Journal of Pathology Informatics|February 29, 2024
Computational pathology: A survey review and the way forwardMahdi S Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc-Huy Trinh, et al.Journal of Pathology Informatics|July 19, 2024
A novel Slide-seq based image processing software to identify gene expression at the single cell levelTh I Götz, X Cong, S Rauber, et al.Pageof 86