Screening for Depression Using Natural Language Processing: Literature Review.

ABSTRACT:

Background

Depression is a prevalent global mental health disorder with substantial individual and societal impact. Natural language processing (NLP), a branch of artificial intelligence, offers the potential for improving depression screening by extracting meaningful information from textual data, but there are challenges and ethical considerations.

Objective

This literature review aims to explore existing NLP methods for detecting depression, discuss successes and limitations, address ethical concerns, and highlight potential biases.

Methods

A literature search was conducted using Semantic Scholar, PubMed, and Google Scholar to identify studies on depression screening using NLP. Keywords included "depression screening," "depression detection," and "natural language

SUBMITTER: Teferra BG 

PROVIDER: S-EPMC11574504 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature