Applications of Machine Learning and Uncertainty Modeling for Real-World Medical Decision-Making
摘要截稿:
全文截稿: 2024-06-02
影响因子: 3.025
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 医学 - 2区
• 小类 : 计算机:信息系统 - 3区
• 小类 : 卫生保健与服务 - 2区
• 小类 : 医学:信息 - 2区
Overview
In recent years, the medical field has seen a surge in available data. This has led to the development of machine learning (ML) systems to help doctors make better decisions. However, these systems have yet to be fully embraced in real-world settings. One key issue is that these systems often struggle with handling uncertainty, limiting their reliability. The aim of this special issue is to explore how ML and uncertainty management methods can be applied in medical decision-making, and how accounting for uncertainty in clinical practice can make ML systems more reliable and safer to use in real-world healthcare settings.
Guest editors:
Dr. Andrea CampagnerIRCCS Galeazzi Orthopaedic Institute
Dr. Elia Mario BiganzoliUniversity of Milan
Dr. Clara Balsano University of L'Aquila
Dr. Cristina CeredaRegional Health Care and Social Agency Fatebenefratelli Sacco