| # PiLA: PPG-based Cardiac Disease Diagnosis Model |
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| ## Overview |
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| This repository provides pretrained and finetuned model weights for PiLA, a deep learning framework for cardiac disease diagnosis from photoplethysmography (PPG) signals. |
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| The model supports multimodal physiological inputs, including: |
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| * PPG |
| * VPG (velocity PPG) |
| * APG (acceleration PPG) |
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| ## Files |
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| * `pretrain_model.pth`: self-supervised pretrained weights |
| * `model_best.pth`: finetuned model for downstream diagnosis |
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| ## Code |
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| Source code is available at: |
| https://github.com/EZAIJ/PiLA-PPG |
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| ## Data |
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| Due to privacy and ethical constraints, the dataset is not publicly available. |
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| ## Notes |
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| * The released weights do not contain any identifiable or participant-level data. |
| * This model is provided for research use only. |
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| ## Paper |
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| https://arxiv.org/abs/2602.04266 |
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