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Review
. 2020 Sep;585(7824):193-202.
doi: 10.1038/s41586-020-2669-y. Epub 2020 Sep 9.

Illuminating the dark spaces of healthcare with ambient intelligence

Albert Haque  1 , Arnold Milstein  2 , Li Fei-Fei  3   4
Affiliations
Review

Illuminating the dark spaces of healthcare with ambient intelligence

Albert Haque et al. Nature. 2020 Sep.

Abstract

Advances in machine learning and contactless sensors have given rise to ambient intelligence-physical spaces that are sensitive and responsive to the presence of humans. Here we review how this technology could improve our understanding of the metaphorically dark, unobserved spaces of healthcare. In hospital spaces, early applications could soon enable more efficient clinical workflows and improved patient safety in intensive care units and operating rooms. In daily living spaces, ambient intelligence could prolong the independence of older individuals and improve the management of individuals with a chronic disease by understanding everyday behaviour. Similar to other technologies, transformation into clinical applications at scale must overcome challenges such as rigorous clinical validation, appropriate data privacy and model transparency. Thoughtful use of this technology would enable us to understand the complex interplay between the physical environment and health-critical human behaviours.

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References

    1. LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015). This paper reviews developments in deep learning and explains common neural network architectures such as convolutional and recurrent neural networks when applied to visual and natural language-processing tasks. - DOI
    1. Jordan, M. I. & Mitchell, T. M. Machine learning: trends, perspectives, and prospects. Science 349, 255–260 (2015).
    1. Esteva, A. et al. A guide to deep learning in healthcare. Nat. Med. 25, 24–29 (2019). This perspective describes the use of computer vision, natural language processing, speech recognition and reinforcement learning for medical imaging tasks, electronic health record analysis, robotic-assisted surgery and genomic research.
    1. Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 44–56 (2019). This review outlines how artificial intelligence is used by clinicians, patients and health systems to interpret medical images, find workflow efficiencies and promote patient self-care. - PubMed
    1. Sutton, R. T. et al. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit. Med. 3, 17 (2020). - PubMed - PMC

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