Predicting adverse events in schizophrenia using digital phenotyping and machine learning: results from the HOPE-S observational study
C Heaukulani*, A Sim*, Z. Yang, T Buddhika, NAA Rashid, X Wang, F Ping, R Verghese, JH Yip, X Zhang, S Zheng, YF Quek, S Basu, KW Lee, C Tang, S Verma, RJT Morris, J Lee
Submitted May 2024
*joint first authorship
Deploying AI Methods for Mental Health in Singapore: From Mental Wellness to Serious Mental Health Conditions
C Heaukulani, YS Phang, JH Weng, J Lee, and RJT Morris
AAAI 2024 Machine Learning for Cognitive and Mental Health Workshop
[paper]
Utility of wrist wearable and smartphone-based digital phenotyping in psychosis
Z Yang*, C Heaukulani*, A Sim, T Buddhika, NAA Rashid, X Wang, S Zheng, YF Quek, S Basu, KW Lee, C Tang, S Verma, RJT Morris, J Lee
Submitted Sep 2023
*joint first authorship
Psychosis-focused mHealth interventions: a systematic mapping review of their characteristics and evaluated outcomes
PY Loh, L Martinengo, C Heaukulani, XY Tan, M Hng, YY Cheah, RJT Morris, LT Car, and J Lee
Submitted Sep 2023
[paper]
Experience of use, perceived usability and impact of a workplace digital mental wellness platform “mindline at work”: a mixed methods study
S Yoon, H Goh, XC Low, JH Weng, and C Heaukulani
Submitted Aug 2023
[paper]
Perceptions of a Digital Mental Health Platform Among Participants With Depressive Disorder, Anxiety Disorder, and Other Clinically Diagnosed Mental Disorders in Singapore: Usability and Acceptability Study
YS Phang, C Heaukulani, W Martanto, RJT Morris, MM Tong, and R Ho
JMIR Human Factors, 10, e42167. Mar 2023.
[paper]
Mental Wellness Self-care in Singapore with mindline.sg: A Framework for the Development of a Digital Mental Health Platform for Behaviour Change
JH Weng JH, Y Hu, C Heaukulani, C Tan, JK Chang, YS Phang, P Rajendram, WM Tan, WC Loke, and RJT Morris
To appear, JMIR 2024. (Preprint originally posted Jan 2023.)
[paper]
Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study
NAA Rashid, W Martanto, Z Yang, X Wang, C Heaukulani, N Vouk, T Buddhika, Y Wei, W Verma, C Tang, RJT Morris, and J Lee
BMJ open, 11(10), e046552. Oct 2021.
[paper]
Association between wrist wearable digital markers and clinical status in Schizophrenia
W Martanto, Y Koh, Z Yang, C Heaukulani, X Wang, NAA Rashid, A Sim, S Zheng, C Tang, S Verma, RJT Morris, and J Lee
General Hospital Psychiatry (Letter to the Editor), Vol. 70, 134-136, 2021.
[paper]
HOPES -- An integrative digital phenotyping platform for data collection, monitoring and machine learning
X Wang, N Vouk, C Heaukulani, T Bhuddika, W Martanto, J Lee, and RJT Morris
Journal of Medical Internet Research, 23(3), e23984. Mar 2021.
[paper]
Machine Learning
Modelling financial volume curves with hierarchical Poisson processes
C. Heaukulani, Abhinav Pandey, and Lancelot F. James
ArXiv preprint: arXiv:2406.19402, June 2024.
[paper]
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
C. Heaukulani and Mark van der Wilk
NeurIPS, 2019.
[paper]
[code]
Variational inference for neural network matrix factorization and its application to stochastic blockmodeling
Onno Kampman and C. Heaukulani
ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data
[paper]
[code]
The combinatorial structure of beta negative binomial processes
C. Heaukulani and Daniel M. Roy
Bernoulli, Vol. 22, No. 4, 2301--2324, 2016.
[paper]
Dynamic probabilistic models for latent feature propagation in social networks
C. Heaukulani and Zoubin Ghahramani
ICML, 2013.
[paper]
Latent Dirichlet reallocation for term swapping
C. Heaukulani, J. Le Roux, and J. Hershey
International Workshop on Statistical Machine Learning for Speech Processing (IWSML). March 2012.
[paper]