Literature DB >> 31702559

The Last Mile: Where Artificial Intelligence Meets Reality.

Enrico Coiera1.   

Abstract

Although much effort is focused on improving the technical performance of artificial intelligence, there are compelling reasons to focus more on the implementation of this technology class to solve real-world applications. In this "last mile" of implementation lie many complex challenges that may make technically high-performing systems perform poorly. Instead of viewing artificial intelligence development as a linear one of algorithm development through to eventual deployment, there are strong reasons to take a more agile approach, iteratively developing and testing artificial intelligence within the context in which it finally will be used. ©Enrico Coiera. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.11.2019.

Entities:  

Keywords:  artificial intelligence; implementation sceince; sociotechnical systems

Mesh:

Year:  2019        PMID: 31702559     DOI: 10.2196/16323

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  10 in total

1.  Clinical management of sepsis can be improved by artificial intelligence: yes.

Authors:  Matthieu Komorowski
Journal:  Intensive Care Med       Date:  2019-12-13       Impact factor: 17.440

2.  A Graphical Toolkit for Longitudinal Dataset Maintenance and Predictive Model Training in Health Care.

Authors:  Eric Bai; Sophia L Song; Hamish S F Fraser; Megan L Ranney
Journal:  Appl Clin Inform       Date:  2022-02-16       Impact factor: 2.342

3.  Can Unified Medical Language System-based semantic representation improve automated identification of patient safety incident reports by type and severity?

Authors:  Ying Wang; Enrico Coiera; Farah Magrabi
Journal:  J Am Med Inform Assoc       Date:  2020-10-01       Impact factor: 4.497

4.  Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study.

Authors:  Stina Matthiesen; Søren Zöga Diederichsen; Mikkel Klitzing Hartmann Hansen; Christina Villumsen; Mats Christian Højbjerg Lassen; Peter Karl Jacobsen; Niels Risum; Bo Gregers Winkel; Berit T Philbert; Jesper Hastrup Svendsen; Tariq Osman Andersen
Journal:  JMIR Hum Factors       Date:  2021-11-26

5.  Physicians' Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle-Income Countries.

Authors:  Srinivas Emani; Angela Rui; Hermano Alexandre Lima Rocha; Rubina F Rizvi; Sergio Ferreira Juaçaba; Gretchen Purcell Jackson; David W Bates
Journal:  JMIR Cancer       Date:  2022-04-07

6.  Machine learning for real-time aggregated prediction of hospital admission for emergency patients.

Authors:  Zella King; Joseph Farrington; Martin Utley; Enoch Kung; Samer Elkhodair; Steve Harris; Richard Sekula; Jonathan Gillham; Kezhi Li; Sonya Crowe
Journal:  NPJ Digit Med       Date:  2022-07-26

7.  Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

Authors:  Julian C Hong; Neville C W Eclov; Sarah J Stephens; Yvonne M Mowery; Manisha Palta
Journal:  BMC Bioinformatics       Date:  2022-09-30       Impact factor: 3.307

Review 8.  Bridging the "last mile" gap between AI implementation and operation: "data awareness" that matters.

Authors:  Federico Cabitza; Andrea Campagner; Clara Balsano
Journal:  Ann Transl Med       Date:  2020-04

9.  Celebrating 20 Years of Open Access and Innovation at JMIR Publications.

Authors:  Gunther Eysenbach
Journal:  J Med Internet Res       Date:  2019-12-23       Impact factor: 5.428

Review 10.  Machine learning techniques for mortality prediction in emergency departments: a systematic review.

Authors:  Amin Naemi; Thomas Schmidt; Marjan Mansourvar; Mohammad Naghavi-Behzad; Ali Ebrahimi; Uffe Kock Wiil
Journal:  BMJ Open       Date:  2021-11-02       Impact factor: 2.692

  10 in total

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