Natural Language Processing in Diagnostic Texts from Nephropathology.

ABSTRACT:

Introduction

This study investigates whether it is possible to predict a final diagnosis based on a written nephropathological description-as a surrogate for image analysis-using various NLP methods.

Methods

For this work, 1107 unlabelled nephropathological reports were included. (i) First, after separating each report into its microscopic description and diagnosis section, the diagnosis sections were clustered unsupervised to less than 20 diagnostic groups using different clustering techniques. (ii) Second, different text classification methods were used to predict the diagnostic group based on the microscopic description section.

Results

The best clustering results (i) could be achieved with HDBSCAN, using BoW-based feature extraction methods. Based on keywords, the

SUBMITTER: Legnar M 

PROVIDER: S-EPMC9325286 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature