Clinical characteristics of dome-shaped macula in mild myopic or non-myopic eyes
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A hybrid multi model artificial intelligence approach for glaucoma screening using fundus images
Glaucoma, a leading cause of blindness, requires accurate early detection. We present an AI-based Glaucoma Screening (AI-GS) network comprising six lightweight deep learning models (total size: 110 MB) that analyze fundus images to identify early structural signs such as optic disc cupping, hemorrhages, and nerve fiber layer defects. The segmentation of the optic cup and disc closely matches that of expert ophthalmologists. AI-GS achieved a sensitivity of 0.9352 (95% CI 0.9277–0.9435) at 95% specificity. In real-world testing, sensitivity dropped to 0.5652 (95% CI 0.5218–0.6058) at ~0.9376 specificity (95% CI 0.9174–0.9562) for the standalone binary glaucoma classification model, whereas the full AI-GS network maintained higher sensitivity (0.8053, 95% CI 0.7704–0.8382) with good specificity (0.9112, 95% CI 0.8887–0.9356). The sub-models in AI-GS, with enhanced capabilities in detecting early glaucoma-related structural changes, drive these improvements. With low computational demands and tunable detection parameters, AI-GS promises widespread glaucoma screening, portable device integration, and improved understanding of disease progression.
Long-term macular atrophy growth in neovascular age-related macular degeneration: influential factors and role of genetic variants
This retrospective cohort study aimed to assess the long-term growth and associated risk factors of macular atrophy (MA) in eyes with neovascular age-related macular degeneration (nAMD) treated with intravitreal anti-vascular endothelial growth factor (anti-VEGF) compounds.
Evaluation of electrical impedance spectroscopy of bovine eyes for early detection of uveal melanoma
Uveal melanoma is the most common primary intraocular cancer in adults and is an aggressive malignancy with risk to vision and survival. Early detection and timely management of tumors may help preserve vision and reduce mortality rate but is challenging as many tumors are asymptomatic until they become large. Here, we studied the electrical properties of eyes to investigate a novel method for potentially detecting small intraocular tumors. We used finite element analysis to simulate the impact of uveal melanoma tumors on electrical impedance and current density in eye models. We also measured the impedance and current flow in the presence of inserted tissue simulating an intraocular tumor in enucleated bovine eyes and eyes in bovine head ex vivo. Our results showed that a 5 mm-diameter mass was detected inside a 32-mm diameter bovine eye by the impedance analyzer.
D5 digital circular workflow: five digital steps towards matchmaking for material reuse in construction
The intersection of digital transformation and circular construction practices presents significant potential to mitigate environmental impacts through optimised material reuse. We propose a five-step (D5) digital circular workflow that integrates these digital innovations towards reuse, validated through real-world case studies. We assessed a variety of digital tools for enhancing the reuse of construction materials, including digital product passports, material classification assisted by artificial intelligence (AI), reality capture, computational design, design inspired by generative AI, digital fabrication techniques, extended reality, and blockchain technology. Using action research through a multiple case study approach, we disassembled several buildings that were set for demolition and subsequently designed and executed construction projects using the salvaged materials. Our findings indicate that digital transformation for detection, disassembly, distribution, design, and finally deployment significantly support the application of circular economy principles. We demonstrate the potential of the proposed workflow for industry implementation and scalability.
Differentiation of anterior chamber pigment and inflammatory cells using swept-source optical coherence tomography: a cross-sectional study
We aimed to investigate the potential of anterior segment OCT (AS-OCT) in differentiating anterior chamber (AC) pigment and inflammatory cells.
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