A5060202890- Glaucoma and retinal disorders
- Retinal Imaging and Analysis
- Retinal Diseases and Treatments
- Digital Imaging for Blood Diseases
- Clusterin in disease pathology
- Corneal surgery and disorders
- Biomedical and Engineering Education
- Adipose Tissue and Metabolism
- Cell Image Analysis Techniques
- Cancer-related molecular mechanisms research
- Spaceflight effects on biology
- Flavonoids in Medical Research
- Artificial Intelligence in Healthcare and Education
Menzies School of Health Research
2023-2024
University of Tasmania
2019-2024
QIMR Berghofer Medical Research Institute
2023
Genome-wide association studies have recently uncovered many loci associated with variation in intraocular pressure (IOP). Artificial intelligence (AI) can be used to interrogate the effect of specific genetic knockouts on morphology trabecular meshwork cells (TMCs) and thus, IOP regulation.
Abstract Introduction Primary open angle glaucoma (POAG) is a leading cause of blindness globally. Characterized by progressive retinal ganglion cell degeneration, the precise pathogenesis remains unknown. Genome-wide association studies (GWAS) have uncovered many genetic variants associated with elevated intraocular pressure (IOP), one key risk factors for POAG. We aimed to identify and morphological variation that can be attributed trabecular meshwork (TMC) dysfunction raised IOP in...
ObjectiveAn enlarged cup-to-disc ratio (CDR) is a hallmark of glaucomatous optic neuropathy. Manual assessment the CDR may be less accurate and more time-consuming than automated methods. Here, we sought to develop validate deep learning–based algorithm automatically determine from fundus images.DesignAlgorithm development for estimating using data population-based observational study.ParticipantsA total 181 768 images United Kingdom Biobank (UKBB), Drishti_GS, EyePACS.MethodsFastAI PyTorch...
ABSTRACT Objective An enlarged cup-to-disc ratio (CDR) is a hallmark of glaucomatous optic neuropathy. Manual assessment CDR may be inaccurate and time-consuming. Herein we sought to develop validate deep-learning-based algorithm automatically determine from fundus images. Design Algorithm development for estimating using data population-based observational study. Participants A total 184,580 images the UK Biobank, Drishti_GS, EyePACS. Main Outcome Measures The area under receiver operating...
<title>Abstract</title> <bold>Objective</bold> Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for screening using fundus images could enhance early and accurate disease detection. Herein, we developed validated generalized deep-learning-based algorithm images. <bold>Methods</bold> The glaucomatous data were collected from 20 publicly accessible...
Abstract Importance Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for screening using fundus images could enhance early and accurate disease detection. Objective To develop validate generalised deep-learning-based algorithm image. Design, setting participants The glaucomatous data were collected from 20 publicly accessible databases worldwide,...
Abstract Space is considered to be the most inhospitable environment known man. A lack of oxygen, microgravity, extremes temperature, ionising radiation and inability grow food being only a few challenges that space exploration may pose those brave enough travel there. (1) Consequently, astronauts encountered numerous health risks primarily due effects microgravity as well psychological impacts isolation confinement. (2,3) Because this, it imperative wellbeing monitored closely ensure their...
ABSTRACT PURPOSE The exact pathogenesis of primary open-angle glaucoma (POAG) is poorly understood. Genome-wide association studies (GWAS) have recently uncovered many loci associated with variation in intraocular pressure (IOP); a crucial risk factor for POAG. Artificial intelligence (AI) can be used to interrogate the effect specific genetic knockouts on morphology trabecular meshwork cells (TMCs), regulatory IOP. METHODS Sixty-two genes at fifty-five IOP were knocked out TMC lines. All...
Abstract Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection paramount yet challenging, particularly in resource-limited settings. Herein, we sought to develop and validate generalised deep-learning-based algorithm for screening using fundus images. We collected glaucomatous data from 20 publicly accessible databases worldwide selected the best-performing model pre-trained models. The top-performing was further trained classifying healthy images Fastai PyTorch...
ABSTRACT INTRODUCTION Primary open angle glaucoma (POAG) is a leading cause of blindness globally. Characterised by progressive retinal ganglion cell degeneration, the precise pathogenesis remains unknown. Genome-wide association studies (GWAS) have uncovered many genetic variants associated with elevated intraocular pressure (IOP), one key risk factors for POAG. This study sought to investigate morphological and transcriptional consequences perturbation genes at IOP loci in trabecular...