免疫组化抗原大模型数据集

该数据集涵盖了抗原信息、抗体信息、染色过程、染色结果、病理数据、临床信息等字段。具体包括：抗原名称：抗原的名称；抗原种类：抗原的分类；抗体名称：用于免疫组化染色的抗体的名称；抗体类型：抗体的类型；抗体特异性：抗体对特定抗原的结合特异性描述；染色协议：用于染色的详细步骤；染色结果评分：对染色结果的评分；阳性细胞数：染色结果中阳性细胞的数量；阳性面积比例：阳性区域占整个样本区域的比例；染色强度：染色结果的强度；病理类型：肿瘤的病理类型；病理分期：根据肿瘤的大小、转移情况等进行的病理分期；临床特征：患者的临床信息；治疗方案：患者接受的治疗方案；治疗效果：根据免疫组化结果和其他数据，预测治疗的效果。

This dataset encompasses multiple fields such as antigen information, antibody information, staining protocol, staining results, pathological data, and clinical information. The specific contents are as follows: Antigen name: the name of the target antigen; Antigen category: the classification of the antigen; Antibody name: the name of the antibody utilized for immunohistochemical staining; Antibody type: the subtype or category of the antibody; Antibody specificity: a detailed description of the binding specificity of the antibody to the specific antigen; Staining protocol: the step-by-step detailed procedures for the staining experiment; Staining result score: the score assigned to the staining outcome; Number of positive cells: the count of positively stained cells in the staining result; Positive area ratio: the proportion of the positively stained area to the total area of the sample; Staining intensity: the intensity of the staining reaction; Pathological type: the pathological subtype of the tumor; Pathological stage: the pathological staging determined based on tumor size, metastasis status and other relevant factors; Clinical features: the clinical information of the patient; Treatment plan: the treatment regimen received by the patient; Treatment effect: the predicted treatment efficacy based on immunohistochemical results and other relevant data.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于免疫组化技术的医学数据集，主要用于肿瘤诊断、分型、预后评估和治疗反应预测。它包含抗原信息、抗体信息、染色结果、病理数据和临床信息等关键字段，支持临床决策和个性化治疗。数据集以Excel格式提供，适用于机器学习和深度学习模型开发。