Machine learning techniques for decision support in anesthesia

被引：0
|
作者：
Caelen, Olivier [1 ]
Bontempi, Gianluca [1 ]
Barvais, Luc [2 ]
机构：
[1] Univ Libre Bruxelles, Dept Informat, Machine Learning Grp, Brussels, Belgium
[2] Univ Libre Bruxelles, Fac Med, Service Anesthesiologie Reamination, Brussels, Belgium
来源：
ARTIFICIAL INTELLIGENCE IN MEDICINE, PROCEEDINGS | 2007年 / 4594卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The growing availability of measurement devices in the operating room enables the collection of a huge amount of data about the state of the patient and the doctors' practice during a surgical operation. This paper explores the possibilities of generating, from these data, decision support rules in order to support the daily anesthesia procedures. In particular, we focus on machine learning techniques to design a decision support tool. The preliminary tests in a simulation setting are promising and show the role of computational intelligence techniques in extracting useful information for anesthesiologists.
引用
收藏
页码：165 / 169
页数：5
相关论文
共 50 条
  • [1] A Review of Machine Learning Techniques using Decision Tree and Support Vector Machine
    Somvanshi, Madan
    Tambade, Shital
    Chavan, Pranjali
    Shinde, S. V.
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2016,
  • [2] Opal: an implementation science tool for machine learning clinical decision support in anesthesia
    Bishara, Andrew
    Wong, Andrew
    Wang, Linshanshan
    Chopra, Manu
    Fan, Wudi
    Lin, Alan
    Fong, Nicholas
    Palacharla, Aditya
    Spinner, Jon
    Armstrong, Rachelle
    Pletcher, Mark J.
    Lituiev, Dmytro
    Hadley, Dexter
    Butte, Atul
    [J]. JOURNAL OF CLINICAL MONITORING AND COMPUTING, 2022, 36 (05) : 1367 - 1377
  • [3] Opal: an implementation science tool for machine learning clinical decision support in anesthesia
    Andrew Bishara
    Andrew Wong
    Linshanshan Wang
    Manu Chopra
    Wudi Fan
    Alan Lin
    Nicholas Fong
    Aditya Palacharla
    Jon Spinner
    Rachelle Armstrong
    Mark J. Pletcher
    Dmytro Lituiev
    Dexter Hadley
    Atul Butte
    [J]. Journal of Clinical Monitoring and Computing, 2022, 36 : 1367 - 1377
  • [4] Decision Support System for Diabetes Mellitus through Machine Learning Techniques
    Rashid, Tarik A.
    Abdulla, Saman. M.
    Abdulla, Rezhna. M.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (07) : 170 - 178
  • [5] A Systematic Review of Applications of Machine Learning Techniques for Wildfire Management Decision Support
    Bot, Karol
    Borges, Jose G.
    [J]. INVENTIONS, 2022, 7 (01)
  • [6] Combining satellite data and Machine Learning techniques for irrigation Decision Support Systems
    Termite, Loris Francesco
    Garinei, Alberto
    Marini, Andrea
    Marconi, Marcello
    Biondi, Lorenzo
    [J]. 2019 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (METROAGRIFOR), 2019, : 291 - 296
  • [7] Two machine-learning techniques for mining solutions of the ReleasePlanner™ decision support system
    Du, Gengshen
    Ruhe, Guenther
    [J]. INFORMATION SCIENCES, 2014, 259 : 474 - 489
  • [8] Architecture for Machine Learning Techniques to Enable Augmented Cognition in the Context of Decision Support Systems
    Martinez, David
    [J]. FOUNDATIONS OF AUGMENTED COGNITION: ADVANCING HUMAN PERFORMANCE AND DECISION-MAKING THROUGH ADAPTIVE SYSTEMS, 2014, 8534 : 148 - 156
  • [9] Machine Learning and Decision Support in Critical Care
    Johnson, Alistair E. W.
    Ghassemi, Mohammad M.
    Nemati, Shamim
    Niehaus, Katherine E.
    Clifton, David A.
    Clifford, Gari D.
    [J]. PROCEEDINGS OF THE IEEE, 2016, 104 (02) : 444 - 466
  • [10] Editorial: Machine Learning and Decision Support in Stroke
    Liebeskind, David S.
    Scalzo, Fabien
    [J]. FRONTIERS IN NEUROLOGY, 2020, 11
12345