一个关于大的数据集及其在CT成像中的相关发现
Doaa Obeidat1, Anas Bsoul1,2, Malak Abdullah3
1Department of Computer Engineering, Jordan University of Science and Technology, P.O. Box 3030 Irbid 22110 Jordan.
Data in brief
|October 27, 2025
概括
这项研究引入了一个新的,开放式的CT扫描数据集,用于训练人工智能模型来诊断脊髓大病及其原因. 本资源旨在促进扩大和相关疾病的早期检测和治疗.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能在医学中的应用
背景情况:
- 大,或大,是严重疾病的关键指标,如肝病和血液癌症.
- 计算机断层扫描 (CT) 是脊髓巨变评估的标准,但人工智能集成提供了对潜在原因的更深入的见解.
- 有限的真实世界数据集阻碍了开发强大的人工智能模型来诊断脊髓大病.
研究的目的:
- 引入多样化,开放式访问的CT扫描数据集,用于脊髓大病研究.
- 促进人工智能驱动模型的开发,用于检测,评估和确定大的原因.
- 为医学学生研究脊柱大病提供一个教育资源.
主要方法:
- 在阿卜杜拉国王大学医院收集了248个未识别的成年人CT扫描和患者数据的数据集.
- 数据集包括有或没有大的病例,涵盖肝硬化,淋巴瘤和白血病等疾病.
- 这些数据通过Zenodo数据库公开提供.
主要成果:
- 该数据集包括248个成年患者的CT扫描 (42%为女性,平均年龄为48.2岁).
- 它包括多种壮症和相关疾病的不同病例,如肝硬化,淋巴瘤,白血病,骨髓增殖性瘤和血症.
- 该数据集现在可以用于研究和教育目的.
结论:
- 这种开放访问的脊髓大病数据集的可用性解决了研究资源的关键缺口.
- 预计这项资源将加速人工智能诊断工具的开发,用于脊髓大病及其相关病理.
- 该数据集将支持临床实践和医疗教育在脏疾病方面的进展.
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