Natural language processing for kidney ultrasound analysis: correlating imaging reports with chronic kidney disease diagnosis.

ABSTRACT:

Introduction

Natural language processing (NLP) has been used to analyze unstructured imaging report data, yet its application in identifying chronic kidney disease (CKD) features from kidney ultrasound reports remains unexplored.

Methods

In a single-center pilot study, we analyzed 1,068 kidney ultrasound reports using NLP techniques. To identify kidney echogenicity as either "normal" or "increased," we used two methods: one that looks at individual words and another that analyzes full sentences. Kidney length was identified as "small" if its length was below the 10th percentile. Nephrologists reviewed 100 randomly selected reports to create the reference standard (ground truth) for initial model training followed by model validation on an independent set of 100 reports.

R

SUBMITTER: Wang C 

PROVIDER: S-EPMC12322987 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature