Artificial intelligence and kidney transplantation

Organization: Baishideng Publishing Group Inc
Journey Stage: (*) Not Part of Journey Stages
Organization Type: Society or Professional Organization
Use Case(s): Allocation, Clinical Intervention, Diagnostics, Patient Experience
Country: Turkey

Pulled from PubMed

Nurhan Seyahi 1, Seyda Gul Ozcan 2

Artificial intelligence and its primary subfield, machine learning, have started to gain widespread use in medicine, including the field of kidney transplantation. We made a review of the literature that used artificial intelligence techniques in kidney transplantation. We located six main areas of kidney transplantation that artificial intelligence studies are focused on: Radiological evaluation of the allograft, pathological evaluation including molecular evaluation of the tissue, prediction of graft survival, optimizing the dose of immunosuppression, diagnosis of rejection, and prediction of early graft function. Machine learning techniques provide increased automation leading to faster evaluation and standardization, and show better performance compared to traditional statistical analysis. Artificial intelligence leads to improved computer-aided diagnostics and quantifiable personalized predictions that will improve personalized patient care.

Key Contact:

Nurhan
Seyahi
Professor at Cerrahpaşa Medical Faculty

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