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The Contribution of Artificial Intelligence in Achieving the Sustainable Development Goals (SDGs): What Can Eye Health Can Learn From Commercial Industry and Early Lessons From the Application of Machine Learning in Eye Health Programmes.
Sawers, Nicholas; Bolster, Nigel; Bastawrous, Andrew.
  • Sawers N; The International Centre for Eye Health (ICEH), London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Bolster N; Peek Vision, London, United Kingdom.
  • Bastawrous A; The International Centre for Eye Health (ICEH), London School of Hygiene and Tropical Medicine, London, United Kingdom.
Front Public Health ; 9: 752049, 2021.
Article in English | MEDLINE | ID: covidwho-1775940
ABSTRACT
Achieving The United Nations sustainable developments goals by 2030 will be a challenge. Researchers around the world are working toward this aim across the breadth of healthcare. Technology, and more especially artificial intelligence, has the ability to propel us forwards and support these goals but requires careful application. Artificial intelligence shows promise within healthcare and there has been fast development in ophthalmology, cardiology, diabetes, and oncology. Healthcare is starting to learn from commercial industry leaders who utilize fast and continuous testing algorithms to gain efficiency and find the optimum solutions. This article provides examples of how commercial industry is benefitting from utilizing AI and improving service delivery. The article then provides a specific example in eye health on how machine learning algorithms can be purposed to drive service delivery in a resource-limited setting by utilizing the novel study designs in response adaptive randomization. We then aim to provide six key considerations for researchers who wish to begin working with AI technology which include collaboration, adopting a fast-fail culture and developing a capacity in ethics and data science.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence Type of study: Experimental Studies Limits: Humans Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.752049

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence Type of study: Experimental Studies Limits: Humans Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.752049