Nitesh123123/my-distiset-25792e43

该数据集是通过distilabel工具生成的，包含了一个`pipeline.yaml`文件，用于重现生成该数据集的流程。数据集的结构包括`prompt`、`completion`和`system_prompt`三个字段，分别表示提示、完成和系统提示。数据集的内容主要围绕生成一个包含10万条放射学报告的数据集，这些报告分为两类：一类是包含一些异常发现但最终印象为阴性的报告，另一类是所有发现均为正常且最终印象为阴性的报告。每个报告都遵循标准化的结构，包括成像方式、患者人口统计信息、发现、印象和建议。

This dataset was created using the distilabel tool and includes a `pipeline.yaml` file to reproduce the pipeline that generated it. The dataset structure consists of three fields: `prompt`, `completion`, and `system_prompt`, representing the prompt, completion, and system prompt respectively. The dataset content focuses on generating a dataset of 100,000 radiology reports, divided into two categories: reports with some abnormal findings but a negative final impression, and reports with entirely normal findings and a negative final impression. Each report follows a standardized structure, including imaging modality, patient demographics, findings, impression, and advice.