Literature DB >> 21871406

Advanced integrated real-time clinical displays.

Grant H Kruger1, Kevin K Tremper.   

Abstract

Intelligent medical displays have the potential to improve patient outcomes by integrating multiple physiologic signals, exhibiting high sensitivity and specificity, and reducing information overload for physicians. Research findings have suggested that information overload and distractions caused by patient care activities and alarms generated by multiple monitors in acute care situations, such as the operating room and the intensive care unit, may produce situations that negatively impact the outcomes of patients under anesthesia. This can be attributed to shortcomings of human-in-the-loop monitoring and the poor specificity of existing physiologic alarms. Modern artificial intelligence techniques (ie, intelligent software agents) are demonstrating the potential to meet the challenges of next-generation patient monitoring and alerting.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21871406     DOI: 10.1016/j.anclin.2011.05.004

Source DB:  PubMed          Journal:  Anesthesiol Clin        ISSN: 1932-2275


  5 in total

Review 1.  A Review of Visual Representations of Physiologic Data.

Authors:  Rishikesan Kamaleswaran; Carolyn McGregor
Journal:  JMIR Med Inform       Date:  2016-11-21

2.  Anesthesiology Control Tower-Feasibility Assessment to Support Translation (ACTFAST): Mixed-Methods Study of a Novel Telemedicine-Based Support System for the Operating Room.

Authors:  Teresa Murray-Torres; Aparna Casarella; Mara Bollini; Frances Wallace; Michael S Avidan; Mary C Politi
Journal:  JMIR Hum Factors       Date:  2019-04-23

3.  Auditing of Monitoring and Respiratory Support Equipment in a Level III-C Neonatal Intensive Care Unit.

Authors:  Elena Bergon-Sendin; Carmen Perez-Grande; David Lora-Pablos; Javier De la Cruz Bertolo; María Teresa Moral-Pumarega; Gerardo Bustos-Lozano; Carmen Rosa Pallas-Alonso
Journal:  Biomed Res Int       Date:  2015-10-19       Impact factor: 3.411

4.  Continuous stroke volume estimation from aortic pressure using zero dimensional cardiovascular model: proof of concept study from porcine experiments.

Authors:  Shun Kamoi; Christopher Pretty; Paul Docherty; Dougie Squire; James Revie; Yeong Shiong Chiew; Thomas Desaive; Geoffrey M Shaw; J Geoffrey Chase
Journal:  PLoS One       Date:  2014-07-17       Impact factor: 3.240

5.  Faster clinical response to the onset of adverse events: A wearable metacognitive attention aid for nurse triage of clinical alarms.

Authors:  Daniel C McFarlane; Alexa K Doig; James A Agutter; Lara M Brewer; Noah D Syroid; Ranjeev Mittu
Journal:  PLoS One       Date:  2018-05-16       Impact factor: 3.240

  5 in total

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