Machine learning in medicine: a practical introduction to natural language processing.

ABSTRACT:

Background

Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of written text into interpretable datasets that can be analysed by statistical and machine learning (ML) models. The purpose of this paper is to provide a practical introduction to contemporary techniques for the analysis of text-data, using freely-available software.

Methods

We performed three NLP experiments using publicly-available data obtained from medicine review websites. First, we conducted lexicon-based sentiment analysis on open-text patient reviews of four drugs: Levothyroxine, Viagra, Oseltamivir and Apixaban. Next, we used

SUBMITTER: Harrison CJ 

PROVIDER: S-EPMC8325804 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature