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Can I read Current Challenges in Adopting Machine Learning to Critical Care and Emergency Medicine on EtoBox?
Current Challenges in Adopting Machine Learning to Critical Care and Emergency Medicine by Cyra-Yoonsun Kang; Joo Heung Yoon is a Medicine article available to read on EtoBox.
What is Current Challenges in Adopting Machine Learning to Critical Care and Emergency Medicine about?
Over the past decades, the field of machine learning (ML) has made great strides in medicine. Despite the number of ML-inspired publications in the clinical arena, the results and implications are not readily accepted at the bedside. Although ML is very powerful in deciphering hidden patterns in complex critical care and emergency medicine data, various factors including data, feature generation, model design, performance assessment, and limited implementation could affect the utility of the research. In this short review, a series of current challenges of adopting ML models to clinical research will be discussed.
Who reads Current Challenges in Adopting Machine Learning to Critical Care and Emergency Medicine?
It is typically read by researchers, students, and practitioners in Medicine.
- Author
- Cyra-Yoonsun Kang; Joo Heung Yoon
- Publisher
- The Korean Society of Emergency Medicine
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)