辽宁省Luminal类型判断辅助诊断模型训练数据

通过对样本的数据处理和数据加工，提供给辅助诊断人工智能模型进行训练，帮助人工智能模型更好地理解辽宁省样本场景下的Luminal类型情况，提取特征，发现规律，最终提高诊断人工智能模型的准确性、鲁棒性和泛化能力。1数据采集：通过正式合作协议，从医疗机构取得匿名化的样本临床数据，包括术后Ki67增殖指数，同时还要获取系统内乳腺癌类型数据；2数据处理：对数据进行检查核对，确保所有数据去标志化，处于完全匿名化状态且不可还原的状态，将没有病理结果的数据去除，对异常数据进行清洗去除，对部分缺失数据进行生成式补充；3数据加工：基于原始数据以及算法规则，生成乳腺癌的Luminal类型标记，具体判断规则为：如果乳腺癌类型为Luminal型， 同时Ki67增殖指数小于14，则肿瘤类型标记为Luminal A型，反之为Luminal B型。

This dataset is subjected to sample data processing and curation for training auxiliary diagnostic artificial intelligence (AI) models, aiming to help the AI models better understand the Luminal subtype scenarios in clinical samples from Liaoning Province, extract features and discover patterns, so as to ultimately improve the accuracy, robustness and generalization ability of the diagnostic AI models.
1. Data Collection: Through formal cooperation agreements, anonymized clinical sample data is obtained from medical institutions, including postoperative Ki67 proliferation index and breast cancer subtype data from the institutional system;
2. Data Processing: Data is inspected and verified to ensure that all data is de-identified, fully anonymized and irreversibly non-identifiable. Data without pathological results is removed, abnormal data is cleaned and eliminated, and generative imputation is performed for partially missing data;
3. Data Curation: Based on the raw data and algorithmic rules, Luminal subtype labels for breast cancer are generated. The specific classification rules are as follows: if the breast cancer subtype is Luminal and the Ki67 proliferation index is less than 14, the tumor is labeled as Luminal A subtype; otherwise, it is labeled as Luminal B subtype.

搜集汇总

数据集介绍

特点

该数据集包含150条辽宁省Luminal类型乳腺癌的临床数据，用于辅助诊断模型训练。数据经过匿名化处理和清洗，并根据Ki67增殖指数标记Luminal类型（A型或B型）。