TOPOLOGICAL DATA ANALYSIS METHODS AND REUSABLE DATASETS IN MENTAL HEALTH RESEARCH
Abstract
This systematic review maps how topological data analysis has been used in mental-health research, with emphasis on analytical methods, data representations, and reusable datasets. PubMed, arXiv, and reference lists were searched under PRISMA 2020 criteria. Thirty-eight eligible reports were identified. Persistent homology dominated multiscale connectome analysis, whereas Mapper was mainly used for subgroup discovery. ADHD-200 and ABIDE were the most reused open resources. Progress now depends on harmonized, cross-disorder benchmarks that document filtration choices, preprocessing, and site effects.
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