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New Technologies to Improve Healthcare in Low- and Middle-income Countries: Global Grand Challenges Satellite Event, Oxford University Clinical Research Unit, Ho Chi Minh City, 17th-18th September 2019

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Date 2020 Sep 3
PMID 32864470
Citations 5
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Abstract

We report the outputs of a satellite event in Ho Chi Minh City, Vietnam, organized as part of the "2 Global Grand Challenges of Engineering Summit". The event considered challenges and potential solutions for improving low- and middle-income country (LMIC) healthcare systems, with particular reference to critical care.  Participants from key regional and local stakeholders in healthcare and engineering discussed how new advances in technology, especially in the field of Artificial Intelligence, could be of potential benefit. This article summarizes the perspectives and conclusions of a group of key stakeholders from LMICs across South and South East Asia.

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References
1.
Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K . Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis. Anesthesiology. 2018; 129(4):663-674. DOI: 10.1097/ALN.0000000000002300. View

2.
Thorsen-Meyer H, Nielsen A, Nielsen A, Kaas-Hansen B, Toft P, Schierbeck J . Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records. Lancet Digit Health. 2020; 2(4):e179-e191. DOI: 10.1016/S2589-7500(20)30018-2. View

3.
Chassagnon G, Vakalopoulou M, Paragios N, Revel M . Artificial intelligence applications for thoracic imaging. Eur J Radiol. 2019; 123:108774. DOI: 10.1016/j.ejrad.2019.108774. View

4.
Singh R, Kalra M, Nitiwarangkul C, Patti J, Homayounieh F, Padole A . Deep learning in chest radiography: Detection of findings and presence of change. PLoS One. 2018; 13(10):e0204155. PMC: 6171827. DOI: 10.1371/journal.pone.0204155. View

5.
Turner H, Van Hao N, Yacoub S, Hoang V, Clifton D, Thwaites G . Achieving affordable critical care in low-income and middle-income countries. BMJ Glob Health. 2019; 4(3):e001675. PMC: 6590958. DOI: 10.1136/bmjgh-2019-001675. View