Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks.

ABSTRACT:

Background

Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task.

Objective

We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient's history of present illness typically occurring in the beginning of a psychiatric initial evaluation note.

Materials and methods

We clean and p

SUBMITTER: Tran T 

PROVIDER: S-EPMC5705423 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature