Xiaohang Wu

Sun Yat-Sen University | SYSU · Zhongshan Ophthalmic Center

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-rela...

Image quality variation is a prominent cause of performance degradation for intelligent disease diagnostic models in clinical applications. Image quality issues are particularly prominent in infantile fundus photography due to poor patient cooperation, which poses a high risk of misdiagnosis. Here, we developed a deep learning-based image quality a...

Data quality issues have been acknowledged as one of the greatest obstacles in medical artificial intelligence research. Here, we present DeepFundus, which employs deep learning techniques to perform multidimensional classification of fundus image quality and provide real-time guidance for on-site image acquisition. We describe steps for data prepa...

Purpose: To probe the dynamic alternations of neural networks in real-time visual processing after visual deprivation (VD) removal. Methods: A prospective cross-sectional study was conducted. Twenty children with a history of early binocular VD caused by congenital cataracts and 20 matched typically developing (TD) children were enrolled. The ev...

Purpose: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images. Design: A diagnostic, cross-sectional, validity and reliability study. Methods: EE-Explorer consists of two models. The triage model was developed from metadata (events,...

Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-world settings. This dataset bias proves a major driver of AI system dysfunction. Inspired by the design...

Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and ocular movements, can assist ophthalmic practice, applying these features to real-world screening r...

Aims To characterise retinal microvascular alterations in the eyes of pregnant patients with anaemia (PA) and to compare the alterations with those in healthy controls (HC) using optical coherence tomography angiography (OCTA). Methods This nested case‒control study included singleton PA and HC from the Eye Health in Pregnancy Study. Fovea avascul...

Purpose: To assess the performance of a deep learning (DL) algorithm for evaluating and supervising cataract extraction using phacoemulsification with intraocular lens (IOL) implantation based on cataract surgery (CS) videos. Materials and methods: DeepSurgery was trained using 186 standard CS videos to recognize 12 CS steps and was validated in...

Medical artificial intelligence (AI) and big data technology have rapidly advanced in recent years, and they are now routinely used for image-based diagnosis. China has a massive amount of medical data. However, a uniform criteria for medical data quality have yet to be established. Therefore, this review aimed to develop a standardized and detaile...

Cataracts are the leading cause of blindness worldwide. Early diagnosis and timely treatment of cataracts can improve patients’ quality of life and reduce healthcare burdens. However, imbalanced distribution of medical resources has limited the coverage of cataract management. Besides, the current standard of management of cataract patients still n...

Background Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically applicable DLS for fundus diseases using data derived from the real world, and externally test the m...

Teleophthalmology, a subfield of telemedicine, has recently been widely applied in ophthalmic disease management, accelerated by ubiquitous connectivity via mobile computing and communication applications. Teleophthalmology has strengths in overcoming geographic barriers and broadening access to medical resources, as a supplement to face-to-face cl...

Infantile cataract is the main cause of infant blindness worldwide. Although previous studies developed artificial intelligence (AI) diagnostic systems for detecting infantile cataracts in a single center, its generalizability is not ideal because of the complicated noises and heterogeneity of multicenter slit-lamp images, which impedes the applica...

Background: To assess associations of high academic performance with ametropia prevalence and myopia development in Chinese schoolchildren. Methods: This multicohort observational study was performed in Guangdong, China. We first performed a cross-sectional cohort analysis of students in grades 1 to 9 from Yangjiang to evaluate the relationship...

Background: Myopia is a complex disease caused by a combination of multiple pathogenic factors. Prevalence trends and developmental patterns of myopia exhibit substantial variability that cannot be clearly assessed using limited sample sizes. This study aims to determine the myopia prevalence over the past 60 years and trace the myopia development...

Background: Lens opacity seriously affects the visual development of infants. Slit-illumination images play an irreplaceable role in lens opacity detection; however, these images exhibited varied phenotypes with severe heterogeneity and complexity, particularly among pediatric cataracts. Therefore, it is urgently needed to explore an effective com...

Purpose Due to population ageing as well as the high prevalence of hypertension and age‐related macular degeneration (AMD) in elderly individuals, and the relationship between hypertension and AMD is unclear. Our research aimed to investigate the association between hypertension, wet AMD (wAMD) and the treatment strategy of wAMD patients affected b...

Background: Human immunodeficiency virus (HIV) infection has become a chronic disease and attracted public attention globally. Population migration was considered hindering the control and management of HIV infection, but limited studies have explored how population mobility could influence the development of HIV-related complications and overall...

Background Cryptophthalmos is characterized by congenital ocular dysplasia with eyelid malformation. The pathogenicity of mutations in genes encoding components of the FRAS1/FREM protein complex is well established, but the underlying pathomechanisms of this disease are still unclear. In the previous study, we generated mice carrying Frem2 R725X/R2...

Background The high prevalence of ocular manifestations (OMs) in patients with human immunodeficiency virus (HIV) infection and chronic diseases such as diabetes has become a global health issue. However, there is still a lack of an appropriate ophthalmic diagnostic procedure for the early detection of OMs in this population, leading to the risk of...

A challenge of chronic diseases that remains to be solved is how to liberate patients and medical resources from the burdens of long-term monitoring and periodic visits. Precise management based on artificial intelligence (AI) holds great promise; however, a clinical application that fully integrates prediction and telehealth computing has not been...

Background: Medical pre-internship plays a crucial role in medical education promoting early involvement of students in clinical setting and helping them explore potential interest of specialty. However, there is currently no specifically designed pre-internship curriculum in China. Using ophthalmology as a pilot field, we have set up a modified o...

Background: Although influencing the severity of postoperative intraocular inflammation of congenital cataract, the developmental characteristics of cytokine profile in the aqueous humor during childhood had not been described. And its relationship with the inflammatory response after intraocular surgery remained unsolved. Methods: Preoperative...

Artificial intelligence (AI) based on deep learning has shown excellent diagnostic performance in detecting various diseases with good-quality clinical images. Recently, AI diagnostic systems developed from ultra-widefield fundus (UWF) images have become popular standard-of-care tools in screening for ocular fundus diseases. However, in real-world...

The management of ophthalmic diseases in the virtual hospital can be implemented and is complementary to those of on-site F2F clinics. Virtual clinical service may be a useful model in the post-COVID-19 pandemic “new normal”.

Background: Lens opacity seriously affects the visual development of infants. Slit-illumination images play an irreplaceable role in lens opacity detection; however, these images exhibited varied phenotypes with severe heterogeneity and complexity, particularly among pediatric cataracts. Therefore, it is urgently needed to explore an effective comp...

The development of artificial intelligence algorithms typically demands abundant high-quality data. In medicine, the datasets that are required to train the algorithms are often collected for a single task, such as image-level classification. Here, we report a workflow for the segmentation of anatomical structures and the annotation of pathological...

Background About 30% of cell lines have been cellular cross-contaminated and misidentification, which can result in invalidated experimental results and unusable therapeutic products. Cell morphology under the microscope was observed routinely, and further DNA sequencing analysis was performed periodically to verify cell line identity, but the sequ...

Background: To investigate the attitude and formal suggestions on talent cultivation in the field of medical artificial intelligence (AI). Methods: An electronic questionnaire was sent to both medical-related field or non-medical field population using the WenJuanXing web-application via social media. The questionnaire was designed to collect: (...

Background: Artificial intelligence (AI) is an increasingly popular tool in medical investigations. However, AI's potential of aiding medical teaching has not been explored. This study aimed to evaluate the effectiveness of AI-tutoring problem-based-learning (PBL) in ophthalmology clerkship and to assess the student evaluations of this module. Me...

Background: The aim of this study was to develop an intelligent system based on a deep learning algorithm for automatically diagnosing fungal keratitis (FK) in in vivo confocal microscopy (IVCM) images. Methods: A total of 2,088 IVCM images were included in the training dataset. The positive group consisted of 688 images with fungal hyphae, and...

Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BCI applications with AI assistance have emerged. Th...

Artificial intelligence (AI) based on machine learning (ML) and deep learning (DL) techniques has gained tremendous global interest in this era. Recent studies have demonstrated the potential of AI systems to provide improved capability in various tasks, especially in image recognition field. As an image-centric subspecialty, ophthalmology has beco...

Aims To compare macular structure and vasculature between neuromyelitis optica spectrum disorder (NMOSD) and primary open angle glaucoma (POAG) using optical coherence tomography angiography. Methods NMOSD patients (n=124) with/without a history of optic neuritis (ON) (NMO+ON: 113 eyes; NMO-ON: 95 eyes), glaucomatous patients (n=102) with early/ad...

Importance Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machine learning methods based on specific corneal parameters. To date, a deep learning algorithm has not...

Purpose: To evaluate the choroidal thickness (CT) in children with congenital aniridia in comparison with age-matched controls. Methods: This was a cross-sectional, observational study that included 64 eyes of 32 children with congenital aniridia (aged 5–12 years) and 80 eyes of 40 healthy subjects who were age-matched. In all subjects, subfoveal c...

Background Color vision is the ability to detect, distinguish, and analyze the wavelength distributions of light independent of the total intensity. It mediates the interaction between an organism and its environment from multiple important aspects. However, the physicochemical basis of color coding has not been explored completely, and how color p...

Purpose: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images. Methods: A total of 16,827 UWF images from 11,339 individuals were used to develop the DL system. Three experienced retina specialists were recruited to grade UWF images independently. Three independent data...

Retinal detachment can lead to severe visual loss if not treated timely. The early diagnosis of retinal detachment can improve the rate of successful reattachment and the visual results, especially before macular involvement. Manual retinal detachment screening is time-consuming and labour-intensive, which is difficult for large-scale clinical appl...

Abstract Background Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood blindness. Methods This case-control study was performed in the Zhongshan Ophthalmic Center...

The general public’s attitudes, demands, and expectations regarding medical AI could provide guidance for the future development of medical AI to satisfy the increasing needs of doctors and patients. The objective of this study is to investigate public perceptions, receptivity, and demands regarding the implementation of medical AI. An online quest...

Sensory loss is associated with behavioural changes, but how behavioural dynamics change when a sensory modality is impaired remains unclear. Here, by recording under a designed standardized scenario, the behavioural phenotypes of 4,196 infants who experienced varying degrees of visual loss but retained high behavioural plasticity, we show that beh...

Visual development during early childhood is a vital process. Examining the visual acuity of children is essential for early detection of visual abnormalities, but performing visual examination in children is challenging. Here, we developed a human-in-the-loop deep learning (DL) paradigm that combines traditional vision examination and DL with inte...

Background Ocular manifestation, which occurs in 82·6% patients with HIV/AIDS, affects quality of life and has become a serious global public health problem. However, little attention has been paid to this issue because of its uncertain relationship with survival outcome. We aimed to demonstrate the potential relationship between ocular manifestati...

Background Common diseases are not satisfactorily managed under the current health-care system because of inadequate medical resources and limited accessibility. We aimed to establish and validate a universal artificial intelligence (AI) platform for collaborative management of cataracts involving multilevel clinical scenarios, and explored an AI-b...

Purpose To establish and validate a universal artificial intelligence (AI) platform for collaborative management of cataracts involving multilevel clinical scenarios and explored an AI-based medical referral pattern to improve collaborative efficiency and resource coverage. Methods The training and validation datasets were derived from the Chinese...

BACKGROUND In vitro human cell line models have been widely used for biomedical research to predict clinical response, identify novel mechanisms and drug response. However, one-fifth to one-third of cell lines have been cross-contaminated, which can seriously result in invalidated experimental results, unusable therapeutic products and waste of res...

Objective To characterise the contributing factors that affect medical students’ subspecialty choice and to estimate the extent of influence of individual factors on the students’ decision-making process. Design Systematic review and meta-analysis. Methods A systematic search of the Cochrane Library, ERIC, Web of Science, CNKI and PubMed database...

Background CC-Cruiser is an artificial intelligence (AI) platform developed for diagnosing childhood cataracts and providing risk stratification and treatment recommendations. The high accuracy of CC-Cruiser was previously validated using specific datasets. The objective of this study was to compare the diagnostic efficacy and treatment decision-ma...

Cryptophthalmos is a rare congenital disorder characterized by ocular dysplasia with eyelid malformation. Complete cryptophthalmos is characterized by the presence of continuous skin from the forehead over the eyes and onto the cheek, along with complete fusion of the eyelids. In the present study, we characterized the clinical manifestations of th...

Purpose: We assess the prevalence of spectacle wear and the factors associated with compliance among aphakic infants with congenital cataracts who underwent lens extraction in South China. Methods: Infants aged 3 months to 3 years were enrolled from among participants in the Childhood Cataract Program of the Chinese Ministry of Health (CCPMOH)....

Background Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approache...

Detailed information on cohorts. (DOCX)

The variable contributions of the trained model on the entire Zhongshan Ophthalmic Centre (ZOC) dataset. The feature importance of spherical equivalent (SE), age at examination (AAE), and annual progression rate (APR) is presented. IncMSE, increase in mean square error. (TIF)

The source code of the algorithm training and validation. (PDF)

The datasets of the Guangzhou Outdoor Activity Longitudinal Trial (GOAL) and the Refractive Error Longitudinal Study (RELS). (XLSX)

Demographic characteristics of the 2 population-based datasets. (DOCX)

Detailed information on out-of-bag validation. (DOCX)

Comparative performance of the random forest and other conventional algorithms. Based on the comparative analysis, the random forest (RF) algorithm outperforms the generalised estimating equation (GEE) and the mixed-effects model (ME) regarding the detection of high myopia. (TIF)

Detailed information on conventional algorithms. (DOCX)

Ocular images play an essential role in ophthalmology. Current research mainly focuses on computer-aided diagnosis using slit-lamp images, however few studies have been done to predict the progression of ophthalmic disease. Therefore exploring an effective approach of prediction can help to plan treatment strategies and to provide early warning for...

Temporal sequence data of the slit-lamp images. (ZIP)

Purpose We investigate visual function impairment and ocular structure in patients with unilateral posterior lens opacity, a type of congenital cataract (CC) in our novel CC category system. Methods We studied patients aged 3 to 15 years who were diagnosed with unilateral posterior CC. Best corrected visual acuity (BCVA) and visual evoked potentia...