{"ID":2869146,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.14617","arxiv_id":"2509.14617","title":"HDC-X: Efficient Medical Data Classification for Embedded Devices","abstract":"Energy-efficient medical data classification is essential for modern disease screening, particularly in home and field healthcare where embedded devices are prevalent. While deep learning models achieve state-of-the-art accuracy, their substantial energy consumption and reliance on GPUs limit deployment on such platforms. We present HDC-X, a lightweight classification framework designed for low-power devices. HDC-X encodes data into high-dimensional hypervectors, aggregates them into multiple cluster-specific prototypes, and performs classification through similarity search in hyperspace. We evaluate HDC-X across three medical classification tasks; on heart sound classification, HDC-X is $350\\times$ more energy-efficient than Bayesian ResNet with less than 1% accuracy difference. Moreover, HDC-X demonstrates exceptional robustness to noise, limited training data, and hardware error, supported by both theoretical analysis and empirical results, highlighting its potential for reliable deployment in real-world settings. Code is available at https://github.com/jianglanwei/HDC-X.","short_abstract":"Energy-efficient medical data classification is essential for modern disease screening, particularly in home and field healthcare where embedded devices are prevalent. While deep learning models achieve state-of-the-art accuracy, their substantial energy consumption and reliance on GPUs limit deployment on such platfor...","url_abs":"https://arxiv.org/abs/2509.14617","url_pdf":"https://arxiv.org/pdf/2509.14617v3","authors":"[\"Jianglan Wei\",\"Zhenyu Zhang\",\"Pengcheng Wang\",\"Mingjie Zeng\",\"Zhigang Zeng\"]","published":"2025-09-18T04:46:16Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false,"code_links":[{"ID":609650,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2869146,"paper_url":"https://arxiv.org/abs/2509.14617","paper_title":"HDC-X: Efficient Medical Data Classification for Embedded Devices","repo_url":"https://github.com/jianglanwei/HDC-X","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}