2025 · Scientific Reports, 15(1), 23069
Identifying and characterizing suicide decedent subtypes using deep embedded clustering
Belouali, A., Kitchen, C., Zirikly, A., Nestadt, P., Wilcox, H. C., & Kharrazi, H.
Biomedical Informatics · Mental Health AI
Anas Belouali.Building AI that surfaces high-risk clinical trajectories from longitudinal health data.
Postdoctoral Research Fellow · Center for Population Health IT, Johns Hopkins Bloomberg School of Public Health
Adjunct Faculty · Health Informatics & Data Science Program, Georgetown University
About
Biomedical informatics researcher working on mental health informatics — patient subtyping, suicide risk prediction, and longitudinal analytics from clinical and administrative data. I build, evaluate, and translate AI and statistical models for population health and precision medicine.
Before Hopkins, I led data science at Georgetown's Innovation Center for Biomedical Informatics, building registries for immuno-oncology, NLP pipelines for adverse-event extraction, and a precision-medicine platform integrating multi-omics with clinical records. I teach AI for Health Applications at Georgetown.
A view of the work
Publications, by year and topic
A decade of work — one cell per paper, colored by primary topic.
2026
02
2025
07
2024
02
2023
04
2022
05
2021
03
2020
01
2019
01
2017
01
2016
01
Hover a cell for details · click to open · outlined cells are highlighted work · max 7 papers/year
Selected work
2025 · JAMA Network Open
Identification of temporal condition patterns associated with suicide from claims data using sequence pattern mining
Belouali, A., Kitchen, C., Haroz, E., Lehmann, H., Nestadt, P., Wilcox, H. C., & Kharrazi, H.
2025 · Nature Communications, 16(1), 6274
Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) Challenge
Zenk, M., Baid, U., Pati, S., Linardos, A., Edwards, B., Sheller, M., Foley, P., …, Belouali, A., …, & Yang, H.
2022 · JAMIA Open, 5(2), ooac046
Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction
Belouali, A., Bai, H., Raja, K., Liu, S., Ding, X., & Kharrazi, H.
Now
Current focus
Suicide risk prediction & phenotyping
Using the Maryland Suicide Data Warehouse and large-scale claims data to identify high-risk clinical trajectories, characterize decedent subtypes with deep embedded clustering, and surface temporal condition patterns associated with suicide death.
Digital monitoring & youth mental health
County-level evaluation of digital monitoring tools (e.g., GoGuardian Beacon) used in U.S. K-12 schools to identify students at risk of self-harm, using difference-in-differences and quasi-experimental designs.
Contact
Always interested in collaborations on mental health informatics, suicide prevention research, real-world evidence, and AI for healthcare.