A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning.

Journal: Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Published Date:

Abstract

BACKGROUND: Postpartum depression (PPD) is a disorder that often goes undiagnosed. The development of a screening program requires considerable and careful effort, where evidence-based decisions have to be taken in order to obtain an effective test with a high level of sensitivity and an acceptable specificity that is quick to perform, easy to interpret, culturally sensitive, and cost-effective. The purpose of this article is twofold: first, to develop classification models for detecting the risk of PPD during the first week after childbirth, thus enabling early intervention; and second, to develop a mobile health (m-health) application (app) for the Android(®) (Google, Mountain View, CA) platform based on the model with best performance for both mothers who have just given birth and clinicians who want to monitor their patient's test.

Authors

  • Santiago Jiménez-Serrano
    1 Biomedical Informatics Group, Institute for the Applications of Advanced Information and Communication Technologies (ITACA), Polytechnic University of Valencia , Valencia, Spain .
  • Salvador Tortajada
  • Juan Miguel García-Gómez