癌症诊断治疗预测病理学大模型数据集

该数据集涵盖了患者的个人背景、癌症诊断、治疗方案、治疗效果、不良反应以及复发风险等多个维度。具体包括：患者年龄：患者的年龄；性别：患者的性别；既往病史：患者的既往病史；肿瘤类型：患者的癌症类型；临床分期：根据TNM分期系统（肿瘤大小、淋巴结受累情况、是否转移）对癌症的临床分期；分化程度：肿瘤细胞的分化程度；肿瘤位置：肿瘤所在的位置；肿瘤大小及形态：肿瘤的大小和形态；免疫组化标志物：用于肿瘤标记的免疫组化染色标志物；浸润深度：肿瘤侵入周围组织的深度；基因突变：患者肿瘤中发现的基因突变类型；临床治疗方案：患者接受的治疗方案；治疗效果：患者治疗后的效果，反映了治疗的有效性；不良反应：患者在接受治疗过程中出现的副作用或不良反应；不良生活习惯：患者的不良生活习惯；环境暴露：患者所处的环境因素；复发风险（预测）：基于患者的各项特征（如肿瘤类型、分期、治疗方案等），预测的复发风险类别。

This dataset covers multiple dimensions including patients' personal backgrounds, cancer diagnoses, treatment regimens, treatment outcomes, adverse reactions, and recurrence risks. Specifically, it includes:
Patient Age: the age of the patient;
Patient Sex: the gender of the patient;
Past Medical History: the patient's pre-existing medical conditions;
Tumor Type: the type of cancer the patient has;
Clinical Stage: the clinical staging of cancer based on the TNM staging system (tumor size, lymph node involvement, and presence of metastasis);
Degree of Differentiation: the differentiation level of tumor cells;
Tumor Location: the site where the tumor is located;
Tumor Size and Morphology: the size and morphology of the tumor;
Immunohistochemical Markers: immunohistochemical staining markers used for tumor labeling;
Depth of Invasion: the depth to which the tumor invades surrounding tissues;
Gene Mutations: the types of gene mutations detected in the patient's tumor;
Clinical Treatment Regimen: the treatment regimen received by the patient;
Treatment Outcome: the post-treatment effect of the patient, reflecting the effectiveness of the treatment;
Adverse Reactions: side effects or adverse reactions experienced by the patient during treatment;
Unhealthy Lifestyle Habits: the patient's unhealthy lifestyle habits;
Environmental Exposure: environmental factors to which the patient is exposed;
Recurrence Risk (Predicted): the predicted recurrence risk category based on various patient characteristics such as tumor type, stage, treatment regimen, and other relevant factors.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于癌症病理学的多维度医疗数据集，涵盖了患者个人背景、癌症诊断、治疗方案、治疗效果、不良反应及复发风险等关键信息。它旨在支持癌症相关的临床试验、早期筛查和复发风险预测，通过分析肿瘤类型、分期、基因突变等特征，帮助研究人员评估治疗效果和患者预后。数据集以Excel格式提供，适用于癌症诊断和治疗预测的大模型开发与应用。