Clinical, radiological, and radiomics feature-based explainable machine learning models for prediction of neurological deterioration and 90-day outcomes in mild intracerebral hemorrhage.

Abstract

Authors

• Weixiong Zeng
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Jiaying Chen
  Department of Mathematics and Information Sciences, China Jiliang University, Hangzhou 310018, Zhejiang Province, PR China. Electronic address: 1041074676@qq.com.
• Linling Shen
  Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Genghong Xia
  Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Jiahui Xie
  Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Shuqiong Zheng
  Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Zilong He
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Limei Deng
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Yaya Guo
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Jingjing Yang
  Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University Jinan 250061 China yanyan.jiang@sdu.edu.cn.
• Yijun Lv
  School of Medical and Information Engineering, Gannan Medical University, Ganzhou 341000, Jiangxi, China.
• Genggeng Qin
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
• Weiguo Chen
  Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China. Electronic address: chenweiguo1964@21cn.com.
• Jia Yin
• Qiheng Wu
  Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, China. cris0087@qq.com.

Keywords

External Resources