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Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Nicole A. Cipriani and Alexander Pearson.
Connection Strength

1.125
  1. Deep learning generates synthetic cancer histology for explainability and education. NPJ Precis Oncol. 2023 May 29; 7(1):49.
    View in: PubMed
    Score: 0.235
  2. The impact of site-specific digital histology signatures on deep learning model accuracy and bias. Nat Commun. 2021 07 20; 12(1):4423.
    View in: PubMed
    Score: 0.207
  3. Deep learning prediction of BRAF-RAS gene expression signature identifies noninvasive follicular thyroid neoplasms with papillary-like nuclear features. Mod Pathol. 2021 05; 34(5):862-874.
    View in: PubMed
    Score: 0.198
  4. Mucoepidermoid Carcinoma: A Comparison of Histologic Grading Systems and Relationship to MAML2 Rearrangement and Prognosis. Am J Surg Pathol. 2019 07; 43(7):885-897.
    View in: PubMed
    Score: 0.179
  5. Prospective study evaluating dynamic changes of cell-free HPV DNA in locoregional viral-associated oropharyngeal cancer treated with induction chemotherapy and response-adaptive treatment. BMC Cancer. 2022 Jan 03; 22(1):17.
    View in: PubMed
    Score: 0.053
  6. Risk and response adapted de-intensified treatment for HPV-associated oropharyngeal cancer: Optima paradigm expanded experience. Oral Oncol. 2021 11; 122:105566.
    View in: PubMed
    Score: 0.053
  7. Artificial Intelligence Can Cut Costs While Maintaining Accuracy in Colorectal Cancer Genotyping. Front Oncol. 2021; 11:630953.
    View in: PubMed
    Score: 0.051
  8. Differentiating low and high grade mucoepidermoid carcinoma of the salivary glands using CT radiomics. Gland Surg. 2021 May; 10(5):1646-1654.
    View in: PubMed
    Score: 0.051
  9. Author Correction: Pan-cancer image-based detection of clinically actionable genetic alterations. Nat Cancer. 2020 Nov; 1(11):1129.
    View in: PubMed
    Score: 0.049
  10. Pan-cancer image-based detection of clinically actionable genetic alterations. Nat Cancer. 2020 08; 1(8):789-799.
    View in: PubMed
    Score: 0.048
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.