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@@ -65,6 +65,16 @@ If you find this dataset useful in your work, please consider citing it:
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  ## 💡 Motivation
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  Machine learning models in real-world clinical settings must detect and reason about anomalies they have **never seen during training**. Current benchmarks mostly focus on known, curated categories—collapsing evaluation back into a **closed-set** problem and overstating model robustness.
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- ## 📦 Usage
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-
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- ```python
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- from datasets import load_dataset
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- dataset = load_dataset("Ano-2090/Nova")
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- ```
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-
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- ---
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  ## ⚠️ Intended Use
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+ ## 📦 Usage
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+ ```python
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+ from datasets import load_dataset
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+ dataset = load_dataset("Ano-2090/Nova")
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+ ```
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+ [Run in Colab](https://colab.research.google.com/github/Ano-2090/Nova/blob/main/example.ipynb)
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+ ---
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  ## 💡 Motivation
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  Machine learning models in real-world clinical settings must detect and reason about anomalies they have **never seen during training**. Current benchmarks mostly focus on known, curated categories—collapsing evaluation back into a **closed-set** problem and overstating model robustness.
 
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  ## ⚠️ Intended Use
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