急性髓系白血病精准医学可解释人工智能数据表2
急性髓系白血病精准医学可解释AI补充数据表，涵盖319例离体肿瘤样本、122种药物筛选与全外显子测序，用于药物反应预测。
基本信息
资源简介
急性髓系白血病精准医学可解释人工智能数据表2
【一句话概览】
本数据集是 figshare 公开的文本数据集，收录 1 个文件、合计 4.07 MB，主题涵盖 biomarkers、treatment selection、assignation problem、explainable artificial intelligence、drug repositioning，可用于医学自然语言处理（实体识别、信息抽取等），CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf》。配套论文《Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia》发表于 Cancer Discovery（2021），DOI：10.1158/2159-8290.CD-21-0410。源站首次发布：2022-09-29。
【数据内容】
源站原始描述：Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of “black box” in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while…
【数据结构与技术规格】
文件数 1 个，合计 4.07 MB。DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf：application/pdf，4.07 MB。数据集 DOI：10.3389/fimmu.2022.977358.s002。
【主题与分类】
源站学科分类：Transplantation Immunology、Tumour Immunology、Immunology not elsewhere classified、Immunology、Veterinary Immunology、Animal Immunology。主题标签：biomarkers、treatment selection、assignation problem、explainable artificial intelligence、drug repositioning、large-scale screening、ex-vivo experiment、drug sensitivity。
【适用方向】
文本类数据可用于医学自然语言处理，如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet_2_Explainable_artificial_intelligence_for_precision_medicine_in_acute_myeloid_leukemia_pdf/21226289
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Gimeno, Marian; San José-Enériz, Edurne; Villar, Sara; Agirre, Xabier; Prosper, Felipe; Rubio, Angel; et al. (2022). DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf. Frontiers. Dataset
【使用注意】
· 源站最后修改于 2023-06-16，引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取（Figshare）
- 源站标题：DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf
- DOI：10.3389/fimmu.2022.977358.s002
- 发布日期：2022-09-29
- 文件数：1 个
- 文件总体积：4.07 MB
- 源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet_2_Explainable_artificial_intelligence_for_precision_medicine_in_acute_myeloid_leukemia_pdf/21226289
命令行下载
curl -L -o "DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf" "https://ndownloader.figshare.com/files/37647038"
文件清单
DataSheet_2_Explainable artificial intelligence for precision medicine in acute myeloid leukemia.pdf（4.07 MB）
文件总体积 4.07 MB（源站 API 实测）。
数据说明
Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of “black box” in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while guaranteeing that predictions are interpretable and robust. We applied MOM to an acute myeloid leukemia (AML) cohort of 319 ex-vivo tumor samples with 122 screened drugs and WES. MOM returned a therapeutic strategy based on the FLT3, CBFβ-MYH11, and NRAS status, which predicted AML patient response to Quizartinib, Trametinib, Selumetinib, and Crizotinib. We successfully validated the results in three different large-scale screening experiments. We believe that XAI will help healthcare providers and drug regulators better understand AI medical decisions.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fimmu.2022.977358.s002（source: https://frontiersin.figshare.com/articles/dataset/DataSheet_2_Explainable_artificial_intelligence_for_precision_medicine_in_acute_myeloid_leukemia_pdf/21226289）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
