Current Applications and Developments of Natural Language Processing in Kidney Transplantation: A Scoping Review

Area of Science:

• Artificial Intelligence
• Medical Informatics
• Nephrology

Background:

• Natural Language Processing (NLP) is an AI subfield enabling computers to process human language.
• NLP tools are increasingly vital in modern life and medical research.
• Their application in kidney transplantation medicine is rapidly expanding.

Purpose of the Study:

• To conduct a scoping review of current and future applications of NLP in kidney transplantation.
• To evaluate the impact of NLP on diagnosis, outcome prediction, and organ utilization.
• To assess NLP's role in public perception and policy-making for transplant care.

Main Methods:

• Electronic literature search on PubMed, EMBASE, and Scopus.
• Inclusion of ten studies after independent review and conflict resolution.
• Analysis of NLP applications in clinical and research settings within kidney transplantation.

Main Results:

• NLP aids in early renal disease diagnosis and predicts graft loss/complications.
• NLP can predict organ viability, potentially improving organ utilization.
• Analysis of social media and news comments using NLP gauges public perception and informs policy.

Conclusions:

• NLP tools are significantly impacting kidney transplantation medicine.
• Potential exists to improve early diagnosis, predict outcomes, and enhance organ utilization.
• NLP is poised to revolutionize renal transplantation with wider EHR adoption and technological advancements.