Advanced calibration of mortality prediction on cardiovascular disease using feature-based artificial neural network
作者：
Highlights：
• Developed a novel neural network for CVD mortality prediction with clinical data.
• Proposed a more time-efficient feature-based artificial neural network (ANN).
• Investigated feature representation to improve ANN for practical guideline.
• Boosted calibration of neural networks and enabled model to make less mistakes.
• Made model updates in clinical context more accessible, flexible and reliable.
摘要
•Developed a novel neural network for CVD mortality prediction with clinical data.•Proposed a more time-efficient feature-based artificial neural network (ANN).•Investigated feature representation to improve ANN for practical guideline.•Boosted calibration of neural networks and enabled model to make less mistakes.•Made model updates in clinical context more accessible, flexible and reliable.
论文关键词：Cardiovascular,Medical claims data,Artificial neural network,Calibration,Feature representation,Autoencoders
论文评审过程：Received 1 November 2021, Revised 14 March 2022, Accepted 25 April 2022, Available online 2 May 2022, Version of Record 11 May 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117393
