Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- PULSE-ECG/ECGInstruct
+- PULSE-ECG/ECGBench
+language:
+- en
+pipeline_tag: image-text-to-text
+tags:
+- medical
+---
+---
+license: apache-2.0
+datasets:
+- PULSE-ECG/ECGInstruct
+language:
+- en
+pipeline_tag: image-text-to-text
+---
+
+# PULSE-7B
+
+Dataset for paper "Teach Multimodal LLMs to Comprehend Electrocardiographic Images".
+
+🌐 Project Page: [https://aimedlab.github.io/PULSE/](https://aimedlab.github.io/PULSE/)
+
+📄 Paper: [need update](https://aimedlab.github.io/PULSE/)
+
+🧑‍💻 Code: [https://github.com/AIMedLab/PULSE](https://github.com/AIMedLab/PULSE)
+
+👩‍⚕️ ECGInstruct(Training): [https://huggingface.co/datasets/PULSE-ECG/ECGInstruct](https://huggingface.co/datasets/PULSE-ECG/ECGInstruct)
+
+⚖️ ECGBench(Testing): [https://huggingface.co/datasets/PULSE-ECG/ECGBench](https://huggingface.co/datasets/PULSE-ECG/ECGBench)
+
+
+## Introduction
+
+We introduce **PULSE-7B**, a multimodal large language model (MLLM) specifically designed for ECG image interpretation. Leveraging the comprehensive **ECGInstruct** dataset, which contains over one million instruction-tuning samples, PULSE-7B is tailored to handle a wide range of ECG-related tasks drawn from diverse data sources. While traditional ECG interpretation methods are often constrained by their reliance on raw physiological signals and limited to specific cardiac conditions, PULSE-7B addresses these limitations by enabling robust interpretation of both printed and digital ECG images, making it especially valuable in resource-limited settings where access to raw signals may be restricted. In conjunction with the introduction of **ECGBench**, a benchmark that includes four key tasks spanning nine datasets, our experiments demonstrate that PULSE-7B establishes new state-of-the-art performance, surpassing general MLLMs with an average accuracy improvement of 15% to 30%. This model showcases the potential to significantly advance ECG image interpretation, providing a more versatile and accurate tool for clinical practice.
+
+Overall performance of PULSE-7B on ECGBench
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/_WI6DO6sjY1SsHF8vn0ZF.jpeg)
+
+## Model Performance
+
+### In-domain
+
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/KmFO7LZpj2K-ASszAdlMF.jpeg)
+
+### Out-of-domain
+
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/DHXAJt-mrNNtrPOCVWZBC.jpeg)
+
+## Case Study
+
+<img src="" alt="https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/4opsQpGP_SiSnfQbZj22b.png" width="700"/>
+<!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/4opsQpGP_SiSnfQbZj22b.png) -->
+<img src="https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/qelm-5ki0g_OEJoSPS8p_.png" alt="ECG Image" width="700"/>
+<!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/qelm-5ki0g_OEJoSPS8p_.png) -->
+<img src="https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/YfKUgi3lsXRu4epinS9BY.png" alt="ECG Image" width="700"/>
+<!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/640701cb4dc5f2846c91d4eb/YfKUgi3lsXRu4epinS9BY.png) -->
+
+## Citation
+If you find this work helpful, please cite out paper:
+
+```bibtex
+```