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Purpose: To generate an overview of global research on artificial intelligence (AI) in eyelid diseases using a bibliometric approach. Methods: All publications related to AI in eyelid diseases from 1900 to 2023 were retrieved from the Web of Science (WoS) Core Collection database. After manual screening, 98 publications published between 2000 and 2023 were finally included. We analyzed the annual trend of publication and citation count, productivity and co-authorship of countries/territories and institutions, research domain, source journal, co-occurrence and evolution of the keywords and co-citation and clustering of the references, using the analytic tool of the WoS, VOSviewer, Wordcloud Python package and CiteSpace. Results: By analyzing a total of 98 relevant publications, we detected that this field had continuously developed over the past two decades and had entered a phase of rapid development in the last three years. Among these countries/territories and institutions contributing to this field, China was the most productive country and had the most institutions with high productivity, while USA was the most active in collaborating with others. The most popular research domains was Ophthalmology and the most productive journals were Ocular Surface. The co-occurrence network of keywords could be classified into 3 clusters respectively concerned about blepharoptosis, meibomian gland dysfunction and blepharospasm. The evolution of research hotspots is from clinical features to clinical scenarios and from image processing to deep learning. In the clustering analysis of co-cited reference network, cluster "0# deep learning" was the largest and latest, and cluster "#5 meibomian glands visibility assessment" existed for the longest time. Conclusions: Although the research of AI in eyelid diseases has rapidly developed in the last three years, there are still gaps in this area. Our findings provide researchers with a better understanding of the development of the field and a reference for future research directions.
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Background: Refractive errors, particularly myopia, are the leading visual disorders worldwide, significantly affecting the quality of life (QOL) even after correction. This scoping review focuses on health-related quality of life (HRQOL) measurements for children and adolescents with refractive errors. Main text: We explored generic and disease-specific HRQOL tools, examining their content, psychometric properties, and the impact of various interventions on QOL. Two English databases-PubMed, Embase, and one Chinese database, CNKI, were searched for relevant studies published from January 2001 to October 2023. Inclusion criteria encompassed studies using standardized instruments to assess the QOL of children aged 0-18 with refractive errors. The review compares prevalent HRQOL measurements, analyzes children's refractive error assessments, and discusses intervention effects on patient QOL. Conclusions: The study underlines the necessity of developing disease-specific QOL instruments for very young children and serves as a practical guide for researchers in this field. The findings advocate for a targeted approach in HRQOL assessment among the pediatric population, identifying critical gaps in current methodologies.
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Oculoplastics is a subspecialty of ophthalmology/dermatology concerned with eyelid, orbital, and lacrimal diseases. Artificial intelligence (AI), with its powerful ability to analyze large data sets, has dramatically benefited oculoplastics. The cutting-edge AI technology is widely applied to extract ocular parameters and to use these results for further assessment, such as screening and diagnosis of blepharoptosis and predicting the progression of thyroid eye disease. AI also assists in treatment procedures, such as surgical strategy planning in blepharoptosis. High efficiency and high reliability are the most apparent advantages of AI, with promising prospects. The possibilities of AI in oculoplastics may lie in three-dimensional modeling technology and image generation. We retrospectively summarize AI applications involving eyelid, orbital, and lacrimal diseases in oculoplastics, and we also examine the strengths and weaknesses of AI technology in oculoplastics.
Subject(s)
Artificial Intelligence , Humans , Lacrimal Apparatus Diseases/diagnosis , Orbital Diseases , Eyelid DiseasesABSTRACT
BACKGROUND: Major depressive disorder (MDD) is a leading mental disorder causing severe impairment. This study was aimed to evaluate sex difference in global MDD incidence by year, age, and socioeconomic status, according to the Global Burden of Disease Study 2019 (GBD 2019). METHODS: Global and national sex-specific incidence estimates of MDD, from 1990 to 2019, in different age groups, were extracted from the GBD 2019. Socioeconomic development index (SDI) as an indicator of national socioeconomic development was used. Absolute (female minus male) and relative (female to male ratio) sex difference in age-standardized incidence rates (ASRs), as well as risk ratios (RR and 95% confidence interval), were computed by year and age. Linear regression analyses were conducted to investigate socioeconomic-associated sex difference in incidence. RESULTS: Absolute and relative sex difference in ASRs showed a slight declining trend during 1990 and 2019, with absolute difference decreasing from 1818.23 to 1602.58, and relative difference decreasing from 1.71 to 1.61. Worldwide, females had a higher risk of MDD than males in 1990 (RR: 1.706 (1.705-1.706)) and 2019 (RR: 1.602 (1.619-1.620)). The highest RRs were observed in the Region of the Americas. Sex difference in incidence rates increased rapidly with age for those under 20 years old. The highest RR (1.913 (1.910-1.915)) was observed in the age group of 10-14. Relative sex difference had a significant positive relationship with SDI (standardized ß = 0.267, P < 0.001). CONCLUSIONS: Despite that slight improvement in sex difference in global MDD incidence has been achieved, sex difference still persists in the past decades, with females always having a higher incidence than males. Greater sex difference was found at younger ages and in more developed countries. The findings highlight the importance of making sex-specific health policy to reduce sex difference in MDD incidence.
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The objective of this study was to investigate the topical iontophoresis of flurbiprofen (FBF) as a means to enhance its local bioavailability and thereby provide an improved and targeted treatment of plantar heel pain. Initial in vitro experiments using porcine ear skin investigated iontophoretic transport of FBF under different conditions. Local FBF biodistribution in the rat paw in vivo was compared after topical or oral administration. Efficacy of pain management was investigated using a plantar incisional model by evaluating pharmacodynamic responses to local pain stimuli. The results demonstrated that iontophoresis of FBF significantly increased cutaneous deposition and transdermal permeation of FBF as compared to passive delivery-it also enabled drug input to be controlled by modulation of current density and drug concentration (r2 > 0.99). Topical iontophoresis of FBF in vivo enabled higher drug levels in skin and muscle in rat plantar aspect and superior pharmacodynamic responses to local pain stimuli, in comparison to oral and passive delivery. In conclusion, short-duration topical iontophoresis of FBF may better help to relieve plantar heel pain than oral or passive administration, which should be of clinical interest.