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NPJ Breast Cancer|August 7, 2021
Collagen fiber orientation disorder from H&E images is prognostic for early stage breast cancer: clinical trial validationHaojia Li, Kaustav Bera, Paula Toro, et al.Cancer Letters|September 25, 2025
AI-informed computational pathology classifier predicts outcomes across treatment modalities in muscle-invasive urothelial carcinomaKamal Hammouda, Naoto Tokuyama, Germán Corredor, et al.Scientific Reports|July 27, 2016
AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue FragmentsGregory Penzias, Andrew Janowczyk, Asha Singanamalli, et al.European Journal of Cancer (Oxford, England : 1990)|March 18, 2026
MuTriM: A multiscale deep learning model integrating longitudinal radiomics and pathomic features for predicting recurrence and adjuvant radiation benefit in breast cancerXiangxue Wang, Liya Chen, Jingwen Sun, et al.Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|March 7, 2020
Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American PatientsHersh K Bhargava, Patrick Leo, Robin Elliott, et al.Journal of Medical Imaging (Bellingham, Wash.)|May 4, 2018
Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomographyMahdi Orooji, Mehdi Alilou, Sagar Rakshit, et al.Npj Imaging|July 4, 2024
CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning modelsFan Fan, Georgia Martinez, Thomas DeSilvio, et al.The Lancet. Digital Health|March 4, 2020
CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in Stage I, II resectable Non-Small Cell Lung Cancer: a retrospective multi-cohort study for outcome predictionPranjal Vaidya, Kaustav Bera, Amit Gupta, et al.European Radiology|September 3, 2020
T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathologyRakesh Shiradkar, Ananya Panda, Patrick Leo, et al.Frontiers in Oncology|September 24, 2021
Radiomic Features Associated With HPV Status on Pretreatment Computed Tomography in Oropharyngeal Squamous Cell Carcinoma Inform Clinical PrognosisBolin Song, Kailin Yang, Jonathan Garneau, et al.Pageof 41