Update README.md

README.md

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 # 🩺 Recurv AI
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-## 📖 **About Us**  
-Recurv AI is dedicated to advancing the healthcare industry through cutting-edge artificial intelligence. Our mission is to empower clinicians, researchers, and patients by developing robust AI models that enhance diagnostics, streamline workflows, and improve patient outcomes.
-
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-
 ## 💡 **Key Projects**  
 
 ### 🏥 [**Recurv-Medical-Dataset**](https://huggingface.co/datasets/RecurvAI/Recurv-Medical-Dataset)
 -   **Description**: A comprehensive dataset comprising question-and-answer pairs from the anamnesis process.
--   **Purpose**:
-    -   To support the development of AI systems capable of understanding and generating context-aware responses during patient interviews.
-    -   To serve as a resource for training and evaluating medical NLP models.
--   **Features**:
-    -   Focused on real-world medical scenarios.
-    -   Structured to ensure data quality and relevance.
     
 ### 🧠 [**Recurv-Medical-Llama**](https://huggingface.co/RecurvAI/Recurv-Medical-Lllama)
 -   **Description**: A fine-tuned version of Llama 3, trained using the [**Recurv-Medical-Dataset**](https://huggingface.co/datasets/RecurvAI/Recurv-Medical-Dataset).
--   **Purpose**:
-    -   To provide state-of-the-art conversational AI for the medical field.
-    -   To assist healthcare professionals by generating accurate, context-aware responses during anamnesis and diagnostic processes.
--   **Capabilities**:
-    -   Medical question answering.
-    -   Contextual reasoning and patient-specific suggestions.
-    -   Support for multi-turn conversations.
----
-
-## 🛠️ **Our Tools & Technologies**  
-- Hugging Face Transformers: NLP models tailored for clinical and biomedical text.  
-- PyTorch and TensorFlow: Building and training state-of-the-art AI models.  
-- DICOM Processing: Specialized libraries for medical imaging workflows.  
 
+### 🏥 [**Recurv-Medical-Dataset**](https://huggingface.co/datasets/RecurvAI/Recurv-Medical-Dataset)
+-   **Description**: A comprehensive clinical dataset covering question-and-answer pairs of the medical knowledge.
+  
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 ## 📢 **Get Involved**  
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-Powered by Hugging Face 🌍  
+Powered by Hugging Face 🌍