Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15182, first published .
Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study

Journals

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  39. Ehrmann D, Harish V, Morgado F, Rosella L, Johnson A, Mema B, Mazwi M. Ignorance Isn't Bliss: We Must Close the Machine Learning Knowledge Gap in Pediatric Critical Care. Frontiers in Pediatrics 2022;10 View
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  42. Harris S, Bonnici T, Keen T, Lilaonitkul W, White M, Swanepoel N. Clinical deployment environments: Five pillars of translational machine learning for health. Frontiers in Digital Health 2022;4 View
  43. Bernstam E, Shireman P, Meric‐Bernstam F, N. Zozus M, Jiang X, Brimhall B, Windham A, Schmidt S, Visweswaran S, Ye Y, Goodrum H, Ling Y, Barapatre S, Becich M. Artificial intelligence in clinical and translational science: Successes, challenges and opportunities. Clinical and Translational Science 2022;15(2):309 View
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  46. Verma A, Pou-Prom C, McCoy L, Murray J, Nestor B, Bell S, Mourad O, Fralick M, Friedrich J, Ghassemi M, Mamdani M. Developing and Validating a Prediction Model For Death or Critical Illness in Hospitalized Adults, an Opportunity for Human-Computer Collaboration. Critical Care Explorations 2023;5(5):e0897 View
  47. van der Vegt A, Scott I, Dermawan K, Schnetler R, Kalke V, Lane P. Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework. Journal of the American Medical Informatics Association 2023;30(7):1349 View
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  55. Davis S, Matheny M, Balu S, Sendak M. A framework for understanding label leakage in machine learning for health care. Journal of the American Medical Informatics Association 2023;31(1):274 View
  56. Nghiem J, Adler D, Estrin D, Livesey C, Choudhury T. Understanding Mental Health Clinicians’ Perceptions and Concerns Regarding Using Passive Patient-Generated Health Data for Clinical Decision-Making: Qualitative Semistructured Interview Study. JMIR Formative Research 2023;7:e47380 View
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Books/Policy Documents

  1. Dube S. An Intuitive Exploration of Artificial Intelligence. View
  2. Ehrmann D, Assadi A, Eytan D, Goodfellow S, Goodwin A, Greer R, Schwartz S, Mazwi M. Pediatric and Congenital Cardiology, Cardiac Surgery and Intensive Care. View
  3. Wright M. Clinical Decision Support and Beyond. View
  4. Wu C, Mathur P. Artificial Intelligence in Clinical Practice. View
  5. Marabelli M. AI, Ethics, and Discrimination in Business. View