AIM: To identify the most-cited articles in ophthalmic epidemiology over the last decade.METHODS: We performed a cited reference search on articles that were included in the ISI Web of Science database using the terms...AIM: To identify the most-cited articles in ophthalmic epidemiology over the last decade.METHODS: We performed a cited reference search on articles that were included in the ISI Web of Science database using the terms "Epidemi*" AND "ophthalm*" AND "population*" during year 2006 to 2016. TOP 100 most cited articles(T100) in ophthalmic epidemiology were short listed and analysed using bibliometrics.RESULTS: These top 100 articles in ophthalmic epidemiology were cited between 61 to 333 times. Of these T100 articles, 36% originated from United States, and 34% were published in the Ophthalmology journal. The three major topics identified were age-related macular degeneration(AMD, n=23), glaucoma(n=16) and visual impairment(n=12). The top-cited article was a study on outdoor activities and its association with the prevalence of myopia in school-aged children, published in 2008. CONCLUSION: This bibliometric analysis provides useful insights into the current development in ophthalmicepidemiology in the past decade and can help recognizing the quality of the researches, discoveries, and trends steering ophthalmic epidemiology.展开更多
The increasing prevalence of diabetes has become a global public health concern in the 21st century.In 2021,it was estimated that 537 million people had diabetes,and this number is projected to reach 643 million by 20...The increasing prevalence of diabetes has become a global public health concern in the 21st century.In 2021,it was estimated that 537 million people had diabetes,and this number is projected to reach 643 million by 2030,and 783 million by 2045[1].Such a huge burden of diabetes brings great challenges in its prevention and management,including early diagnosis,timely interventions,and regular monitoring of risk factor control and complications screening.Continuous self-care support and patient empowerment can enhance clinical and psychobehavioural outcomes[2],although these require additional resources including manpower,infrastructure(hard and technology),and finances.The emergence of digital health technologies(DHTs),especially artificial intelligence(AI),may help address these obstacles and alleviate the burden of diabetes[3].Large language models(LLMs),a generative AI that can accept image and text inputs and produce text outputs,have shown promise in various aspects of medical care.展开更多
基金Supported by National Natural Science Foundation of China(No.81300783)Scientific Research Project of Liaoning Provincial Department of Education(No.LQNK201703)
文摘AIM: To identify the most-cited articles in ophthalmic epidemiology over the last decade.METHODS: We performed a cited reference search on articles that were included in the ISI Web of Science database using the terms "Epidemi*" AND "ophthalm*" AND "population*" during year 2006 to 2016. TOP 100 most cited articles(T100) in ophthalmic epidemiology were short listed and analysed using bibliometrics.RESULTS: These top 100 articles in ophthalmic epidemiology were cited between 61 to 333 times. Of these T100 articles, 36% originated from United States, and 34% were published in the Ophthalmology journal. The three major topics identified were age-related macular degeneration(AMD, n=23), glaucoma(n=16) and visual impairment(n=12). The top-cited article was a study on outdoor activities and its association with the prevalence of myopia in school-aged children, published in 2008. CONCLUSION: This bibliometric analysis provides useful insights into the current development in ophthalmicepidemiology in the past decade and can help recognizing the quality of the researches, discoveries, and trends steering ophthalmic epidemiology.
基金supported by the National Key R&D Program of China(2022YFC2502800 and 2022YFC2407000)the National Natural Science Foundation of China(8238810007,82022012,81870598 and 62272298)+3 种基金the Shanghai Municipal Key Clinical SpecialtyShanghai Research Center for Endocrine and Metabolic Diseases(2022ZZ01002)the Chinese Academy of Engineering(2022-XY-08)the Innovative Research Team of High-level Local Universities in Shanghai(SHSMU-ZDCX20212700)。
文摘The increasing prevalence of diabetes has become a global public health concern in the 21st century.In 2021,it was estimated that 537 million people had diabetes,and this number is projected to reach 643 million by 2030,and 783 million by 2045[1].Such a huge burden of diabetes brings great challenges in its prevention and management,including early diagnosis,timely interventions,and regular monitoring of risk factor control and complications screening.Continuous self-care support and patient empowerment can enhance clinical and psychobehavioural outcomes[2],although these require additional resources including manpower,infrastructure(hard and technology),and finances.The emergence of digital health technologies(DHTs),especially artificial intelligence(AI),may help address these obstacles and alleviate the burden of diabetes[3].Large language models(LLMs),a generative AI that can accept image and text inputs and produce text outputs,have shown promise in various aspects of medical care.
