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Connection

Theresa Thai to Retrospective Studies

This is a "connection" page, showing publications Theresa Thai has written about Retrospective Studies.
Connection Strength

0.225
  1. Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patients. Comput Biol Med. 2024 Apr; 172:108240.
    View in: PubMed
    Score: 0.034
  2. Radiologic Predictors of Increased Number of Necrosectomies During Endoscopic Management of Walled-off Pancreatic Necrosis. J Clin Gastroenterol. 2022 May-Jun 01; 56(5):457-463.
    View in: PubMed
    Score: 0.030
  3. Applying a radiomics-based CAD scheme to classify between malignant and benign pancreatic tumors using CT images. J Xray Sci Technol. 2022; 30(2):377-388.
    View in: PubMed
    Score: 0.030
  4. Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients. Comput Methods Programs Biomed. 2020 Dec; 197:105759.
    View in: PubMed
    Score: 0.027
  5. Relapse Prevention with Tyrosine Kinase Inhibitors after Allogeneic Transplantation for Philadelphia Chromosome-Positive Acute Lymphoblast Leukemia: A Systematic Review. Biol Blood Marrow Transplant. 2020 03; 26(3):e55-e64.
    View in: PubMed
    Score: 0.025
  6. Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy. Acad Radiol. 2017 10; 24(10):1233-1239.
    View in: PubMed
    Score: 0.021
  7. Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome. BMC Med Imaging. 2016 08 31; 16(1):52.
    View in: PubMed
    Score: 0.020
  8. Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis. Acta Radiol. 2016 Sep; 57(9):1149-55.
    View in: PubMed
    Score: 0.019
  9. Measurements of adiposity as clinical biomarkers for first-line bevacizumab-based chemotherapy in epithelial ovarian cancer. Gynecol Oncol. 2014 Apr; 133(1):11-5.
    View in: PubMed
    Score: 0.017
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.