Energy Efficiency of Inference Algorithms for Clinical Laboratory Data Sets: Green Artificial Intelligence Study.

Journal: Journal of medical Internet research
Published Date: Jan 25, 2022

Abstract

BACKGROUND: The use of artificial intelligence (AI) in the medical domain has attracted considerable research interest. Inference applications in the medical domain require energy-efficient AI models. In contrast to other types of data in visual AI, data from medical laboratories usually comprise features with strong signals. Numerous energy optimization techniques have been developed to relieve the burden on the hardware required to deploy a complex learning model. However, the energy efficiency levels of different AI models used for medical applications have not been studied.

Authors

  • Jia-Ruei Yu
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Chun-Hsien Chen
    Department of Information Management, Chang Gung University, Taoyuan City, Taiwan.
  • Tsung-Wei Huang
    Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States.
  • Jang-Jih Lu
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Chia-Ru Chung
    Department of Computer Science and Information Engineering, National Central University.
  • Ting-Wei Lin
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Min-Hsien Wu
    Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan City, Taiwan; Division of Haematology/Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan; Biosensor Group, Biomedical Engineering Research Center, Chang Gung University, Taoyuan City, Taiwan.
  • Yi-Ju Tseng
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.
  • Hsin-Yao Wang
    Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan City, Taiwan.

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