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Volume 101 Issue 4, April 2021

The cover shows image patches cropped from slides that were used as training input in a deep learning system for gynecologic cytopathology. For more information, see the paper by Ke et al, this issue (p 513).

Inside the USCAP Journals

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Review Article

  • Data processing and learning has become a spearhead for the advancement of medicine. Computational pathology is burgeoning subspecialty that promises a better-integrated solution to whole-slide images, multi-omics data and clinical informatics as innovative approach for patient care. This review describes clinical perspectives and discusses the statistical methods, clinical applications, potential obstacles, and future directions of computational pathology.

    • Miao Cui
    • David Y. Zhang
    Review Article
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Mini Review

  • Tandem mass spectrometry can reveal metabolite positional labeling and improve the performance of metabolic flux analysis as long as daughter ions are carefully inspected. When calculating the fluxes, the tandem mass isotopomer distributions as well as the mass isotopomer distributions of parent and daughter ions should all be used to constrain the fluxes in order to achieve the best performance.

    • Yujue Wang
    • Sheng Hui
    • Xiaoyang Su
    Mini Review
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Article

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Technical Report

  • The authors developed a deep-learning-based ductal carcinoma in situ (DCIS) grading system that achieved performance similar to expert observers. To the best of our knowledge, this is the first automated system for the grading of DCIS that could assist pathologists by providing robust and reproducible second opinions on DCIS grade.

    • Suzanne C. Wetstein
    • Nikolas Stathonikos
    • Mitko Veta
    Technical Report Open Access
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Correction

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