Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma: a step towards virtual biopsy.

Journal: International journal of surgery (London, England)
PMID: 38704622

Abstract

OBJECTIVES: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour grading and staging in upper urothelial tract carcinoma patients and to compare these predictions with histopathological diagnosis used as reference standards.

Authors

  • Abdulsalam Alqahtani
    School of Medicine, Centre for Medical Engineering and Technology.
  • Sourav Bhattacharjee
    School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
  • Abdulrahman Almopti
    School of Medicine, Centre for Medical Engineering and Technology.
  • Chunhui Li
    State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China. Electronic address: chunhuili@bnu.edu.cn.
  • Ghulam Nabi
    School of Medicine, Centre for Medical Engineering and Technology, University of Dundee, Dundee DD1 9SY, UK.

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