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Multi-risk factors joint prediction model for risk prediction of retinopathy of prematurity.

Shaobin ChenXinyu ZhaoZhenquan WuKangyang CaoYulin ZhangTao TanChan-Tong LamYanwu XuGuoming ZhangYue Sun
Published in: The EPMA journal (2024)
Combining risk factors with AI in screening programs for ROP could achieve risk prediction of ROP and TR-ROP, detect TR-ROP earlier and reduce the number of ROP examinations and unnecessary physiological stress in low-risk infants. Therefore, combining ROP-related biometric information with AI is a cost-effective strategy for predictive diagnostic, targeted prevention, and personalization of medical services in early screening and treatment of ROP.
Keyphrases
  • risk factors
  • healthcare
  • artificial intelligence
  • public health
  • mental health
  • machine learning
  • cancer therapy
  • drug delivery
  • social media
  • replacement therapy
  • health insurance
  • heat stress