Discipline
Computer Science; Psychology
Methodology
machine learning; natural language processing; social media analysis
Date
21 Jun 2024
Description
This project examines how data gathered via active and passive sensing techniques, including that from smartphones, wearable devices, and social media, can be computationally modeled to assess risk factors for maternal and paternal perinatal mental health, such as depression, stress, and anxiety. Similarly, this project will also aim to develop an intervention referral triaging model using active and passive sensing techniques to assist mothers and fathers with perinatal mental health issues into appropriate support at the right time
Keywords
computational modelling;perinatal mental health;computational social science;social media;mobile computing;digital phenotyping;behavioural biometrics
Would Suit Applicants Who
PhD