GLEAM Multimodal Learner Use Case: HANCOCK dataset

This Zenodo record contains preprocessed, patient-level tabular datasets derived from the public HANCOCK multimodal head-and-neck cancer cohort and configured for binary recurrence prediction. The datasets follow the in-distribution split logic reported in Dörrich et al. (Nature Communications, 2025).

Files: HANCOCK_train_split: in-distribution training cohort and HANCOCK_test_split: in-distribution held-out test cohort

Each CSV row corresponds to a single patient and includes:

1. patient_id: patient identifier

2. split: in-distribution split assignment (consistent with the paper’s evaluation split) 

3. target: recurrence label (binary; endpoint used for recurrence modeling) 

4. clinical/pathological covariates, blood laboratory measurements

5. CD3_image_path, CD8_image_path: filenames/paths for the corresponding CD3/CD8 TMA core images

6. icd_codes: ICD codes in plain text

Imaging availability (CD3/CD8)

The corresponding CD3 and CD8 TMA core images referenced by CD3_image_path and CD8_image_path.

Source publication: https://www.nature.com/articles/s41467-025-62386-6

Raw HANCOCK dataset download portal: https://www.hancock.research.uni-erlangen.org/download

Preprocessing scripts used to generate these split files are available here: GLEAM Use Cases

本Zenodo记录包含经预处理的患者级表格型数据集，其源自公开的HANCOCK多模态头颈癌队列（HANCOCK multimodal head-and-neck cancer cohort），并针对二元复发预测任务进行了配置。
该数据集遵循Dörrich等（2025，《Nature Communications》）发表的研究中所采用的分布内划分逻辑。

数据集包含两个文件：HANCOCK_train_split（分布内训练队列）与HANCOCK_test_split（分布内预留测试队列）。

每条CSV记录对应一名患者，包含以下字段：
1. patient_id：患者唯一标识
2. split：分布内划分分配（与该论文的评估划分保持一致）
3. target：复发标签（二元分类标签，为复发建模所用的研究终点指标）
4. 临床/病理协变量、血液实验室检测指标
5. CD3_image_path、CD8_image_path：对应CD3、CD8免疫组化组织微阵列（Tissue Microarray, TMA）核心图像的文件名/路径
6. icd_codes：纯文本格式的国际疾病分类（International Classification of Diseases, ICD）编码

CD3/CD8影像数据可及性：即由CD3_image_path与CD8_image_path所指向的对应CD3、CD8 TMA核心图像。

来源出版物：https://www.nature.com/articles/s41467-025-62386-6
原始HANCOCK数据集下载门户：https://www.hancock.research.uni-erlangen.org/download
用于生成上述划分文件的预处理脚本可在GLEAM Use Cases处获取。