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      AI to enhance interactive simulation-based training in resuscitation medicine

      proceedings-article
      1 , 2 , 2 , 3 ,   3 , 1
      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)
      Human Computer Interaction Conference
      4 - 6 July 2018
      Digital simulation, Resuscitation medicine, Artificial intelligence, Reinforcement learning
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            Abstract

            When patients become acutely unwell, the ability of frontline healthcare professionals to act quickly and effectively can mean the difference between life and death. High-fidelity simulation is the gold standard by which medics acquire and maintain key resuscitation skills, but the resource-intensive nature of current, face-to-face training limits access to training and allows “skills fade” to creep in. We propose that human computer interaction-based simulations augmented by artificial intelligence could provide a cost-effective alternative to traditional training and allow clinicians much greater access to training. This paper is mostly an in-depth discussion; however, we also present a 3D simulator for resuscitation skills training which we developed using the Unity games physics engine.

            Content

            Author and article information

            Contributors
            Conference
            July 2018
            July 2018
            : 1-4
            Affiliations
            [1 ]Cardiovascular Research Unit, Craigavon Area Hospital, 68 Lurgan Rd, Portadown, BT63 5QQ
            [2 ]Computer Science Research Institute, Ulster University, Shore Road, Newtonabbey, BT37 0QB
            [3 ]Nanotechnology and Integrated BioEngineering Centre, Ulster University, Shore Road, Newtonabbey, BT37 0QB
            Article
            10.14236/ewic/HCI2018.64
            1bd59cc5-eb4e-4a81-a545-10510d13b466
            © Brisk et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            HCI
            32
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            History
            Product

            1477-9358 BCS Learning & Development

            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2018.64
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Digital simulation,Resuscitation medicine,Artificial intelligence,Reinforcement learning

            REFERENCES

            1. Machine learning and radiology Medical image analysis 2012 16 5 933 51

            2. Incidence and outcome of in-hospital cardiac arrest in the United Kingdom National Cardiac Arrest Audit Resuscitation. 2014 85 8 987 92

            3. Clinical practice. Neurologic prognosis after cardiac arrest N Engl J Med 2009;361 6 605 11

            4. Enquiry into Patient Outcome and Death. An acute problem? London: NCEPOD; 2005

            5. National Institute for Health and Clinical Excellence Acutely Ill Patients in Hospital: Recognition and Response to Acute Illness in Hospital National Institute for Health and Clinical Excellence London 2007

            6. Safer Care for the Acutely Ill Patient: Learning from Serious Incidents National Patient Safety Agency London 2007

            7. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study BMJ quality & safety 2012 21 9 737 45

            8. A Automated early warning system for septic shock: the new way to achieve intensive care unit quality improvement? Annals of translational medicine 2017 5 1 17

            9. Part 4: Advanced Life Support: 2015 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations Circulation 2015 132 16 Suppl 1 S84-145

            10. Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates Crit Care Med 2004 32 4 916 21

            11. Low-dose, high-frequency CPR training improves skill retention of in-hospital pediatric providers Pediatrics 2011 128 1 e145-51

            12. Improving the efficiency of advanced life support training: a randomized Controlled Trial Ann Intern Med 2012;157 19 28

            13. Improving the efficiency of advanced life support training: a randomized Controlled Trial Ann Intern Med 2012;157 19 28

            14. Virtual reality training improves operating room performance: results of a randomized, double-blinded study Ann Surg 2002 236 4 458 63

            15. Virtual reality simulation for the operating room: proficiency-based training as a paradigm shift in surgical skills training Ann Surg 2005;241 2 364 72

            16. Relations among conceptual knowledge, procedural knowledge, and procedural flexibility in two samples differing in prior knowledge Developmental psychology 2011 47 6 1525 38

            17. Reinforcement Learning: An Introduction MIT Press Cambridge, MA 1998

            18. 1984 Experiential learning: Experience as the source of learning and development New Jersey Prentice-Hall

            19. Virtu-ALS [COMPUTER / MOBILE APPLICATION] Available at www.virtu-ALS.com. 15 March 2018

            20. M Giving feedback in medical education: verification of recommended techniques J Gen Intern Med 1998;13 2 111 6

            21. Learning people detection models from few training samples In: CVPR. 2011

            22. Evaluation of image features using a photorealistic virtual world In: ICCV(2011

            23. Recognizing materials from virtual examples In European Conference on Computer Vision (ECCV) 2012

            24. Playing Atari with Deep Reinforcement Learning 2013 arXiv:1312.5602

            25. Human level control through deep reinforcement learning Nature 2015 518 529 533

            26. Asynchronous Methods for Deep Reinforcement Learning 2016 arXiv:1602.01783

            27. Policy Gradient [Lecture] University College London 21 Dec 2015 Available at http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html 01 02 2018

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