mtslearn: Machine Learning in Python for Medical Time Series
Medical time-series data captures the dynamic progression of patient conditions, playing a vital role in modern clinical decision support systems. However, real-world clinical data is highly heterogeneous and inconsistently formatted. Furthermore, existing machine learning tools often have steep learning curves and fragmented workflows. Consequently, a significant gap remains between cutting-edge AI technologies and clinical application. To address this, we introduce mtslearn, an end-to-end integrated toolkit specifically designed for medical time-series data. First, the framework provides a unified data interface that automates the parsing and alignment of wide, long, and flat data forma...
| Authors | Zhongheng Jiang, Yuechao Zhao, Donglin Xie et al. |
|---|---|
| Primary category | cs.LG |
| Published | 31 March 2026 |
| Last updated at source | 31 March 2026 |
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