训练机器学习模型以检测基于GC-MS尿液代谢因子的罕见先天性代谢错误 (IEM),用于疾病查

Haomin Li1, Siyuan Gao2, Dan Wu3

  • 1Clinical Data Center, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China.

概括

机器学习模型增强了对代谢先天性错误 (IEM) 查的气色谱-质谱学 (GC-MS) 解释. 这种方法显著提高了从复杂的GC-MS配置文件中识别罕见IEM病例的效率和准确性.