Journal ArticleDOI
The current state of artificial intelligence in ophthalmology.
TLDR
An overview of the basic principles in AI that are essential to the understanding of AI and its application in health care and a descriptive analysis of the current state of AI in various fields of medicine, especially ophthalmology are presented.About:
This article is published in Survey of Ophthalmology.The article was published on 2019-03-01. It has received 115 citations till now. The article focuses on the topics: Human intelligence.read more
Citations
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Journal ArticleDOI
Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy, Third Edition.
Mark B. Horton,Christopher J. Brady,Jerry D. Cavallerano,Michael D. Abràmoff,Gail P. Barker,Michael F. Chiang,Charlene Crockett,Seema Garg,Peter Karth,Yao Liu,Clark D Newman,Siddarth Rathi,Veeral S. Sheth,Paolo S. Silva,Kristen Stebbins,Ingrid Zimmer-Galler +15 more
TL;DR: These guidelines were developed by the Diabetic Retinopathy Telehealth Practice Guidelines Working Group, which consisted of a large number of subject matter experts in clinical applications for telehealth in ophthalmology.
Journal ArticleDOI
Artificial Intelligence in Healthcare and Medicine: Promises, Ethical Challenges and Governance.
TL;DR: The author investigates and discusses three aspects of AI in medicine and healthcare: the application and promises of AI, special ethical concerns pertaining to AI in some frontier fields, and suggestive ethical governance systems.
Journal ArticleDOI
The second information revolution: digitalization brings opportunities and concerns for public health.
TL;DR: It is called for a concerted European response to maximize the benefits of the digital revolution while minimizing the harms, arguably one of the greatest challenges facing the public health community today.
Journal ArticleDOI
Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.
Anna Sophie Mursch-Edlmayr,Wai Siene Ng,Alberto Diniz-Filho,David C Sousa,Louis Arnold,Matthew B. Schlenker,Karla Duenas-Angeles,Pearse A. Keane,Jonathan G Crowston,Hari Jayaram +9 more
TL;DR: The promising levels of diagnostic accuracy reported by AI strategies across the modalities used in clinical practice for glaucoma detection can pave the way for the development of reliable models appropriate for their translation into clinical practice.
Journal ArticleDOI
The best person (or machine) for the job: Rethinking task shifting in healthcare.
May C I van Schalkwyk,Aleš Bourek,Dionne S. Kringos,Luigi Siciliani,Margaret M. Barry,Jan De Maeseneer,Martin McKee +6 more
TL;DR: A position paper is presented based on the work and expertise of the European Commission Expert Panel on Effective ways of Investing in Health that contends that this is over simplistic, and aims to provide a new task shifting framework, informed by relevant evidence, and a series of recommendations.
References
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Journal ArticleDOI
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva,Brett Kuprel,Roberto A. Novoa,Justin M. Ko,Susan M. Swetter,Susan M. Swetter,Helen M. Blau,Sebastian Thrun +7 more
TL;DR: This work demonstrates an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists, trained end-to-end from images directly, using only pixels and disease labels as inputs.
Journal ArticleDOI
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan,Lily Peng,Marc Coram,Martin C. Stumpe,Derek Wu,Arunachalam Narayanaswamy,Subhashini Venugopalan,Kasumi Widner,Tom Madams,Jorge Cuadros,Ramasamy Kim,Rajiv Raman,Philip C. Nelson,Jessica L. Mega,Dale R. Webster +14 more
TL;DR: An algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy and diabetic macular edema in retinal fundus photographs from adults with diabetes.
Journal ArticleDOI
Artificial intelligence in healthcare: past, present and future
Fei Jiang,Yong Jiang,Hui Zhi,Yi Dong,Hao Li,Sufeng Ma,Yilong Wang,Qiang Dong,Haipeng Shen,Yongjun Wang +9 more
TL;DR: The current status of AI applications in healthcare, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation, are surveyed and its future is discussed.
Journal ArticleDOI
Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.
Daniel Shu Wei Ting,Daniel Shu Wei Ting,Carol Y. Cheung,Carol Y. Cheung,Gilbert Lim,Gavin Tan,Gavin Tan,Nguyen Duc Quang,Alfred Tau Liang Gan,Haslina Hamzah,Renata Garcia-Franco,Ian Yew San Yeo,Ian Yew San Yeo,Shu Yen Lee,Shu Yen Lee,Edmund Yick Mun Wong,Edmund Yick Mun Wong,Charumathi Sabanayagam,Charumathi Sabanayagam,Mani Baskaran,Mani Baskaran,Farah Nur Ilyana Mohd Ibrahim,Ngiap Chuan Tan,Ngiap Chuan Tan,Eric A. Finkelstein,Ecosse L. Lamoureux,Ecosse L. Lamoureux,Ian Y. H. Wong,Neil M. Bressler,Sobha Sivaprasad,Rohit Varma,Jost B. Jonas,Mingguang He,Ching-Yu Cheng,Ching-Yu Cheng,Gemmy Cheung,Gemmy Cheung,Tin Aung,Tin Aung,Wynne Hsu,Mong Li Lee,Tien Yin Wong,Tien Yin Wong +42 more
TL;DR: In this evaluation of retinal images from multiethnic cohorts of patients with diabetes, the DLS had high sensitivity and specificity for identifying diabetic retinopathy and related eye diseases.
Proceedings ArticleDOI
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
TL;DR: This work presents two case studies where high-performance generalized additive models with pairwise interactions (GA2Ms) are applied to real healthcare problems yielding intelligible models with state-of-the-art accuracy.
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