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README.md

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+---
+language: en
+license: mit
+pretty_name: Oncology AMIE Dataset
+size_categories:
+- n<1K
+task_categories:
+- text-classification
+- other
+task_ids:
+- text-classification
+- medical-diagnosis
+---
+
+# Oncology AMIE Dataset
+
+## Dataset Description
+
+This dataset contains detailed clinical cases of breast cancer patients, including their age, molecular phenotype (ER/PR/HER2 status), treatment status, special considerations, and ground truth treatment recommendations. The cases are divided into treatment-naive and treatment-refractory categories.
+
+### Dataset Summary
+
+A clinical dataset containing breast cancer cases with their descriptions, molecular phenotypes, and treatment recommendations. The dataset includes both treatment-naive and treatment-refractory cases.
+
+### Features
+
+The dataset includes the following columns:
+- id: Unique identifier for each case
+- type: Whether the case is treatment-naive or treatment-refractory
+- age: Patient age
+- molecular_phenotype: ER/PR/HER2 status
+- treatment_status: Current treatment status
+- special_considerations: Additional clinical considerations
+- description: Detailed case description
+- ground_truth: Expert-provided treatment recommendation
+
+### Usage
+
+This dataset can be used for:
+- Training medical AI systems
+- Clinical decision support development
+- Medical education and training
+- Research in oncology treatment protocols
+
+### Citation
+
+If you use this dataset, please cite the original paper:
+```
+@article{palepu2024exploring,
+  title={Exploring Large Language Models for Specialist-level Oncology Care},
+  author={Palepu, Anil and Dhillon, Vikram and Niravath, Polly and Weng, Wei-Hung and Prasad, Preethi and Saab, Khaled and Tanno, Ryutaro and Cheng, Yong and Mai, Hanh and Burns, Ethan and others},
+  journal={arXiv preprint arXiv:2411.03395},
+  year={2024}
+}
+```