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Molecular Biomarkers & Diagnosis

ISSN: 2155-9929

Open Access

Yahya Alsalman

Department of Clinical Laboratory Sciences, University of Hafr Al Batin, Hafr Al Batin 39831, Saudi Arabia

Publications
  • Mini Review   
    Artificial Intelligence in Bladder Cancer Diagnosis and Treatment
    Author(s): Yahya Alsalman*

    As medical science and technology advance toward the "big data" era, a multi-dimensional dataset pertaining to medical diagnosis and treatment becomes available for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and have a high degree of redundancy. As a result, extensive data processing is widely recommended before feeding the dataset into the mathematical model. Artificial intelligence techniques, such as machine learning and deep learning algorithms based on artificial neural networks and their variants, are being used in this context to generate a precise and cross-sectional illustration of clinical data. Datasets derived from prostate-specific antigen, MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring in prostate cancer pa.. Read More»
    DOI: 10.37421/2155-9929.2022.13.546

    Abstract HTML PDF

Google Scholar citation report
Citations: 2054

Molecular Biomarkers & Diagnosis received 2054 citations as per Google Scholar report

Molecular Biomarkers & Diagnosis peer review process verified at publons

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