CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12567 > Article
Paper
6 March 2023 Towards breastfeeding self-efficacy and postpartum depression estimation based on analysis of free-speech interviews through natural language processing
Luz Itzel Valdeolivar-Hernandez, Maria Eugenia Flores Quijano, Juan Carlos Echeverria-Arjonilla, Jorge Perez-Gonzalez, Omar Piña-Ramirez
Author Affiliations +
Proceedings Volume 12567, 18th International Symposium on Medical Information Processing and Analysis; 125670T (2023) https://doi.org/10.1117/12.2669883
Event: 18th International Symposium on Medical Information Processing and Analysis, 2022, Valparaíso, Chile
Abstract
Edinburgh Postpartum Depression (EPDS) and Breastfeeding Self-Efficacy (BSES) scales are standardized questionnaires to screen for postpartum depression and breastfeeding performance self-perception. On the other hand, Natural Language Processing (NLP) is a machine learning technique that analyses the human language to extract relevant and computer-interpretable information. In this work we proposed the application of an NLP toolchain that includes a typical preprocessing stage and the probabilistic topic modeling performed through the Latent Dirichlet Allocation (LDA) to find out the two most relevant topics within each of six study groups (low, medium, and high scores of BSES and EPDS). Each topic LDA-modeled consisted of 30-word/terms (tokens) which are organized in Venn diagrams, contrasting the mutually exclusive tokens within the low and high scores on each scale. Coherence and log-Perplexity topic modeling performance metrics, were computed. We found that LDA-models have distinguishable tokens between low and high scores of the BSES and EPDS. However, the most remarkable findings were two subset of tokens, one related to newborn care and another to newborn intake, respectively correlated to low and high postpartum depression risk according to EPDS.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Luz Itzel Valdeolivar-Hernandez, Maria Eugenia Flores Quijano, Juan Carlos Echeverria-Arjonilla, Jorge Perez-Gonzalez, and Omar Piña-Ramirez "Towards breastfeeding self-efficacy and postpartum depression estimation based on analysis of free-speech interviews through natural language processing", Proc. SPIE 12567, 18th International Symposium on Medical Information Processing and Analysis, 125670T (6 March 2023); https://doi.org/10.1117/12.2669883
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
;
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 10 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Modeling
Semantics
Statistical analysis
Breast
Data modeling
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top