Member Publications

Have you authored a recent publication in a peer reviewed journal?


We are asking that DPA members who are authors of scientific works published within the last year submit them through our online form so that we can let everybody know about your work! Member publications will be posted on the DPA website. This is a great opportunity to get others to read your work while keeping our members and followers up to date on the latest advances in digital pathology.




  1. At least one DPA member must be listed as an author on the paper
  2. Must be a full paper (not an abstract only) published in a peer reviewed journal
  3. Content must be relevant to the field of digital pathology
  4. Publication date is no earlier than 2019


Please note that all submissions will be reviewed by the DPA Vetting Committee for approval prior to posting. To be considered, please submit the online form. Please note that you must be logged into your DPA Member profile to access the form. 




Adoption of Digital Pathology in Developing Countries: From Benefits to Challenges Journal of the College of Physicians and Surgeons Pakistan
Remote reporting during a Pandemic using Digital Pathology Solution: Experience from a tertiary care cancer center Journal of Pathology Informatics 2021
Digital Pathology Enabling Remote Operations During COVID-19 Pandemic and Beyond - Pathologist Perspective for Future Opportunities  Pakistan Journal of Pathology 2021
Deep Multi-Magnification Networks for multi-class breast cancer image segmentation Computerized Medical Imaging and Graphics 2021
Remote reporting from home for primary diagnosis in surgical pathology: A tertiary oncology center experience during the COVID-19 pandemic Journal of Pathology Informatics 2021
Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media
Modern Pathology
An artificial intellligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study Lancet Digital Health 2020
Emerging Advances to Transform Histopathology Using Virtual Staining
BME Frontiers 2020
Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients
npj Digital Medicine 2020
Explainable AI for Anatomic Pathology Advances in Anatomic Pathology 2020
A machine learning model for detecting invasive ductal carcinoma with Google Cloud AutoML Vision Computers in Biology and Medicine   2020

Brightfield multiplex immunohistochemistry with multispectral imaging

 Laboratory Investigation  2020
The future of digital health with federated learning NPJ Digital Medicine 2020
Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2020
The Role and Financial Implications of Digital Pathology for the System Health [PDF]
Ovidius" University Annals, Economic Sciences Series 2020
Telepathology in Medical Education: Integration of Digital Microscopy in Distance Pathology Education during COVID-19 Pandemic
Journal of Medical Science and Clinical Research 2020
Aligning Reimbursement for Digital Pathology with its Value Journal of Precision Medicine 2020
The Role of Artificial Intelligence for Image Analysis in Surgical Pathology [PDF]
Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics 2020
Automated Analysis of Lymphocytic Infiltration, Tumor Budding, and Their Spatial Relationship Improves Prognostic Accuracy in Colorectal Cancer
Cancer Immunology Research 2019
Video compression to support the expansion of whole-slide imaging into cytology Journal of Medical Imaging 2019

Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer

Cellular Oncology  2019

Deep learning assisted mitotic counting for breast cancer

Laboratory Investigation  2019

Detection of lung cancer lymph node metastases from whole-slide histopathological images using a two-step deep learning approach

The American Journal of Pathology  2019