Ophthatome™: an integrated knowledgebase of ophthalmic diseases for translating vision research into the clinic

Design of Intelligent Diagnosis and Treatment System for Ophthalmic Diseases Based on Deep Neural Network Model

Artificial intelligence (AI) has developed rapidly in the field of ophthalmology. Fundus images have become a research hotspot because they are easy to obtain and rich in biological information. The application of fundus image analysis (AI) in background image analysis has been deepened and expanded. At present, a variety of AI studies have been carried out in the clinical screening, diagnosis, and prognosis of eye diseases, and the research results have been gradually applied to clinical practice. The application of AI in fundus image analysis will improve the situation of lack of medical resources and low diagnosis efficiency. In the future, the research of AI eye images should focus on the comprehensive intelligent diagnosis of various ophthalmic diseases and complex diseases. The focus is to integrate standardized and high-quality data resources, improve algorithm efficiency, and formulate corresponding clinical research plans.

People to policy: The promise and challenges of big data for India

Big data holds great promise to help unravel insights to bridge the gap in human understanding. There has to be an emphasis on the quality of the data points being collected to ensure meaningful analysis. India has made significant strides to lay down a strong framework through the National Digital Health Blueprint and the National Health Stack for the future. There is a need to focus on the first important step of collection of a “good quality” data point through the implementation of electronic medical records by the health care providers. In India, 60 million individuals move below the poverty line every year because of the expenses related to unforeseen illness that adversely affects the individual's welfare and the nation's economic growth. With an out-of-pocket expense rate currently at 70% and the government's health budget at a mere 1.3% of its GDP (gross domestic product), data-driven decisions are the need of the hour for policy making and to ensure equitable, efficient, and excellent delivery of health care. There is a huge potential to harness the power of big data to generate insights to address the four big challenges of health care in India – availability, accessibility, affordability, and acceptability.

Artificial intelligence applications and cataract management: A systematic review

Artificial intelligence (AI)-based applications exhibit the potential to improve the quality and efficiency of patient care in different fields, including cataract management. A systematic review of the different applications of AI-based software on all aspects of a cataract patient's management, from diagnosis to follow-up, was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. All selected articles were analyzed to assess the level of evidence according to the Oxford Centre for Evidence-Based Medicine 2011 guidelines, and the quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation system. Of the articles analyzed, 49 met the inclusion criteria. No data synthesis was possible for the heterogeneity of available data and the design of the available studies. The AI-driven diagnosis seemed to be comparable and, in selected cases, to even exceed the accuracy of experienced clinicians in classifying disease, supporting the operating room scheduling, and intraoperative and postoperative management of complications. Considering the heterogeneity of data analyzed, however, further randomized controlled trials to assess the efficacy and safety of AI application in the management of cataract should be highly warranted.