PCMMD: Plasma Cells for Multiple Myeloma Diagnosis

PCMMD (Plasma Cells for Multiple Myeloma Diagnosis) is an important resource for training and validating Artificial Intelligence (AI) approaches to automate cell identification, supporting studies on MM in developing countries, and discovering approaches regarding other diseases affecting various cell types in diverse populations. The dataset is organized into three sets of cells stained with Wright-Giemsa:

- The first set contains 3,546 cells, with 54% labeled as non-plasma and 46% as plasma cells;
- The second set includes 2,021 cells organized by patients, along with their respective diagnoses;
- The third set comprises 1,615 plasma and 1,931 non-plasma cells, individually segmented without background.

All sets were used to train Deep Neural Network models, whose details and parameters are detailed in the following repository:

https://github.com/LabIA-UFBA/MMDB

PCMMD（Plasma Cells for Multiple Myeloma Diagnosis，多发性骨髓瘤诊断用浆细胞数据集）是用于训练与验证自动化细胞识别人工智能（Artificial Intelligence, AI）方法的重要资源，可为发展中国家开展多发性骨髓瘤（Multiple Myeloma, MM）相关研究提供支撑，同时也可助力探索影响不同人群多种细胞类型的其他疾病的诊疗策略。该数据集分为三组经瑞氏-吉姆萨（Wright-Giemsa）染色的细胞样本：
- 第一组包含3546个细胞，其中54%被标注为非浆细胞，46%为浆细胞；
- 第二组包含2021个细胞，按患者进行分组，并附带每位患者对应的诊断信息；
- 第三组包含1615个浆细胞与1931个非浆细胞，均为单独分割且无背景干扰的样本。
上述三组数据集均被用于训练深度神经网络（Deep Neural Network）模型，相关模型细节与参数可参阅下述代码仓库：
https://github.com/LabIA-UFBA/MMDB