Investigating Intrinsic Bias in Publicly Available Critical Care Datasets for Machine Learning

被引:0
|
作者
Langnas, Erica [1 ]
Fong, Nicholas [1 ]
Law, Tyler [1 ]
Chyan, Arthur [1 ]
Lipnick, Michael [1 ]
Pirracchio, Romain [1 ]
机构
[1] Univ Calif San Francisco, San Francisco, CA 94143 USA
来源
ANESTHESIA AND ANALGESIA | 2023年 / 136卷
关键词
D O I
暂无
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
44
引用
收藏
页码:266 / 267
页数:2
相关论文
共 50 条
  • [1] Scarcity of publicly available oral cancer image datasets for machine learning research
    Sengupta, Namrata
    Sarode, Sachin C.
    Sarode, Gargi S.
    Ghone, Urmi
    ORAL ONCOLOGY, 2022, 126
  • [2] Systematic Review of Publicly Available Critical Care Databases for Retrospective Statistical and Machine Learning Analysis
    Sharma, R.
    Naidoo, S. F.
    Nguyen-Luu, T.
    Fatima, M.
    Bhatnagar, M.
    Mirza, W.
    Elmanzalawi, Y.
    Marshall, K.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2024, 209
  • [3] Predicting within-field cotton yields using publicly available datasets and machine learning
    Leo, Stephen
    De Antoni Migliorati, Massimiliano
    Grace, Peter R.
    AGRONOMY JOURNAL, 2021, 113 (02) : 1150 - 1163
  • [4] A statistical analysis of intrinsic bias of network security datasets for training machine learning mechanisms
    Silva, Joao Vitor V.
    de Oliveira, Nicollas R.
    Medeiros, Dianne S., V
    Lopez, Martin Andreoni
    Mattos, Diogo M. F.
    ANNALS OF TELECOMMUNICATIONS, 2022, 77 (7-8) : 555 - 571
  • [5] A statistical analysis of intrinsic bias of network security datasets for training machine learning mechanisms
    João Vitor V. Silva
    Nicollas R. de Oliveira
    Dianne S. V. Medeiros
    Martin Andreoni Lopez
    Diogo M. F. Mattos
    Annals of Telecommunications, 2022, 77 : 555 - 571
  • [6] Interpretable Machine Learning Model on Thermal Conductivity Using Publicly Available Datasets and Our Internal Lab Dataset
    Barua, Nikhil K.
    Hall, Evan
    Cheng, Yifei
    Oliynyk, Anton O.
    Kleinke, Holger
    CHEMISTRY OF MATERIALS, 2024, 36 (14) : 7089 - 7100
  • [7] Democratizing Deep Learning Research Through Large Publicly Available Datasets and Tools
    Dubis, Adam M.
    Arikan, Mustafa
    Sallo, Ferenc
    Montesel, Andrea
    Hagag, Ahmed M.
    Ahmed, Hend M.
    Book, Marius
    Faatz, Hendrik
    Cicinelli, Maria
    Ongun, Sevim
    Fawzi, Amani A.
    Lilaonitkul, Watjana
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2021, 62 (08)
  • [8] Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool
    Galanty, Maria
    Luitse, Dieuwertje
    Noteboom, Sijm H.
    Croon, Philip
    Vlaar, Alexander P.
    Poell, Thomas
    Sanchez, Clara I.
    Blanke, Tobias
    Isgum, Ivana
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [9] A publicly available crystallisation data set and its application in machine learning
    Pillong, Max
    Marx, Corinne
    Piechon, Philippe
    Wicker, Jerome G. P.
    Cooper, Richard I.
    Wagner, Trixie
    CRYSTENGCOMM, 2017, 19 (27) : 3737 - 3745
  • [10] Towards a comprehensive analysis of agricultural land systems in the EU and US: A critical view on publicly available datasets
    Burchfield, Emily
    Ferro, Marco
    Huettel, Silke
    Lakes, Tobia
    Leonhardt, Heidi
    Niedermayr, Andreas
    Rissing, Andrea
    Seifert, Stefan
    Wesemeyer, Maximilian
    LAND USE POLICY, 2024, 147