Neurai-VN Benchmark: Standardized Machine Learning Models for Multimodal Digital Phenotyping in Mental Health Classification
Digital phenotyping (DP) using smartphones and wearable devices has emerged as a promising approach for assessing mental health, particularly depression and anxiety. However, progress remains difficult to evaluate because of heterogeneity across datasets and inconsistencies in preprocessing pipelines. In this work, we introduce a reproducible machine learning benchmark using the Neurai-VN dataset, a multimodal digital phenotyping dataset collected from 100 Vietnamese adults over two weeks. We define four binary classification tasks evaluated using standardized subject-wise cross-validation. Representative linear, tree-based, and neural baseline models are evaluated systematically across p...
| Authors | Quoc-Cuong Pham, Hoang-Thuy-Duong Vu, Thi-Thanh-Huong Ha et al. |
|---|---|
| Primary category | cs.LG |
| Published | 28 July 2026 |
| Last updated at source | 17 August 2026 |
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