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Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome

  • Published:2019-01 Issue:1 Volume:23 Page:407-415
  • ISSN:2168-2194
  • Container-title:IEEE Journal of Biomedical and Health Informatics
  • language:
  • Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Reamaroon NarathipORCID,Sjoding Michael W.,Lin KaiwenORCID,Iwashyna Theodore J.,Najarian KayvanORCID

Funder

National Science Foundation

National Institute of Health

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning using privileged information with logistic regression on acute respiratory distress syndrome detection;Artificial Intelligence in Medicine;2024-10

2. Feature selection for label distribution learning based on the statistical distribution of data and fuzzy mutual information;Information Sciences;2024-09

3. A systematic review of machine learning models for management, prediction and classification of ARDS;Respiratory Research;2024-06-04

4. The Deep Analysis of Accuracy of Performance Level of NBC Algorithm for Diagnosing BC;2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2024-05-14

5. Segmentation and Classification of Acute Respiratory Distress Syndrome (ARDS) using Deep Learning;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02
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