View clinical trials related to Ophthalmology.
Filter by:Our study presents a detection model predicting a diagnosis of jaundice (clinical jaundice and occult jaundice) trained on prospective cohort data from slit-lamp photos and smartphone photos, demonstrating the model's validity and assisting clinical workers in identifying patient underlying hepatobiliary diseases.
Assessment of aging is central to health management. Compared to chronological age, biological age can better reflect the aging process and health status; however, an effective indicator of biological age in clinical practice is lacking. Human lens accumulates biological changes during aging and is amenable to a rapid and objective assessment. Therefore, the investigators will develop LensAge as an innovative indicator to reveal biological age based on deep learning using lens photographs.
The investigators aim to assess whether bacteriostatic saline provides the same level of anesthesia as traditional local anesthesia while reducing pain associated with medication infusion in minor eyelid procedures
This is an retrospective and prospective multicenter study to develop and validate an artificial intelligent (AI) aided diagnosis, therapeutic effect assessment model including chronic kidney disease (CKD) and dialysis patients starting from April 2009, which is based on ophthalmic examinations (e.g. retinal fundus photography, slit-lamp images, OCTA, etc.) and CKD diagnostic and therapeutic data (routine clinical evaluations and laboratory data), to provide a reliable basis and guideline for clinical diagnosis and treatment.
Virtual reality (VR) is a relatively new, emerging field within healthcare. Studies have analyzed public perceptions of virtual reality in healthcare using social media, but few have actually demonstrated and educated these modalities to communities. Because vision care can be costly and inaccessible, especially in communities with few physicians, this study aims to evaluate whether communities would be open to new technology. For example, it has been determined that 80% of vision loss is preventable with adequate screening technology, a key factor in ameliorating the economic and emotional burden of eye disease. Therefore, through demonstrations and educational presentations by medical students, gaps in understanding perceptions, willingness to adopt, and general demographics of those seeking better eye care will be understood.
Participants (preschool children), because their cognitive ability and anti pressure ability are obviously weaker than adults, most of the children who have this kind of operation and anesthesia stressors will have perioperative anxiety. After eye surgery, they need to bandage their eyes with gauze (single or double), so that the participants are in a state of complete or partial darkness for a certain period of time, which is easy to produce dark phobia. In clinical practice, investigators found that more than 80% of children with advanced ophthalmology were prone to leprosy, resistance, crying and other symptoms after general anesthesia, which brought greater difficulties to nursing. How to improve the cognitive ability of preschool children, reduce the anxiety level of children during the perioperative period, the incidence of postoperative detention and the difficulty of nursing are new topics worthy of exploration.
According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting. Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.
According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting. Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.
The real-world electronic health records (EHR) were derived from the hospitalization of Zhongshan Ophthalmic Center (ZOC) of Sun Yat-sen University from 1998-2020 to investigate the ophthalmology diagnosis and treatment activities.
Biological treatments (BT) are commonly prescribed to treat chronic inflammatory diseases in children. Paradoxical reactions during treatment with a biological agent can be defined as the appearance or exacerbation of a pathological condition that usually responds to this class of drug while treating a patient for another condition. Limited data are available in children treated by BT on cutaneous paradoxical reactions, or any other cutaneous adverse events occurring during treatment. On the contrary, dermatologists tend to see and manage increasing numbers of cutaneous adverse events, including paradoxical reactions. The aim of this project is to describe the incidence of cutaneous adverse events, including cutaneous paradoxical reactions, occurring in the pediatric population, during a treatment by BT given for a chronic inflammatory disease.