Update README.md

README.md

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----
-license: agpl-3.0
-metrics:
-- precision
-pipeline_tag: image-segmentation
-tags:
-- medical
-- tumor
-- healthcare
----
+---
+license: agpl-3.0
+metrics:
+- precision
+pipeline_tag: image-segmentation
+tags:
+- medical
+- tumor
+- healthcare
+base_model:
+- Ultralytics/YOLO11
+---
 # Brain Tumor Segmentation Model with YOLO11
 
+## Disclaimer
+
+**Important Notice**: The Brain Tumor Segmentation Model with YOLO11 is intended **ONLY** for research purposes. This model is **NOT** designed or suitable for medical decision-making or clinical use. The data used to train this model may be **inaccurate, incomplete, or outdated**.
+
+**Do NOT** use this model to diagnose, treat, or manage any health conditions or illnesses. Always consult a qualified healthcare professional for medical advice and diagnosis. The creators and distributors of this model are not responsible for any consequences arising from the use or misuse of this model in medical decision-making.
+
+Use this model with caution and ensure compliance with all relevant regulations and ethical guidelines in your research. The model's predictions and outputs should be interpreted critically and within the context of established medical knowledge.
+
+
 ## Overview
 
 This repository presents a robust brain tumor segmentation model built using the YOLO11 architecture from Ultralytics. Designed for semantic segmentation tasks, this model accurately identifies and delineates brain tumors in medical imaging datasets. Leveraging the power of the YOLO11l-seg variant, it achieves high precision and recall, making it a valuable tool for medical image analysis and research applications.