Related papers: A Clinician-Friendly Platform for Ophthalmic Image…
Early identification of patients at risk of cardiovascular diseases (CVD) is crucial for effective preventive care, reducing healthcare burden, and improving patients' quality of life. This study demonstrates the potential of retinal…
Training models with robust group fairness properties is crucial in ethically sensitive application areas such as medical diagnosis. Despite the growing body of work aiming to minimise demographic bias in AI, this problem remains…
Generalist Medical AI (GMAI) systems have demonstrated expert-level performance in biomedical perception tasks, yet their clinical utility remains limited by inadequate multi-modal explainability and suboptimal prognostic capabilities.…
The diagnosis of oral diseases presents a problematic clinical challenge, characterized by a wide spectrum of pathologies with overlapping symptomatology. To address this, we developed Clinical Semantic Intelligence (CSI), a novel…
Retinopathy of Prematurity (ROP) is a potentially blinding eye disorder because of damage to the eye's retina which can affect babies born prematurely. Screening of ROP is essential for early detection and treatment. This is a laborious and…
Despite its high prevalence, anemia is often undetected due to the invasiveness and cost of screening and diagnostic tests. Though some non-invasive approaches have been developed, they are less accurate than invasive methods, resulting in…
A variety of vision ailments are associated with geographic atrophy (GA) in the foveal region of the eye. In current clinical practice, the ophthalmologist manually detects potential presence of such GA based on fundus autofluorescence…
The growing burden of myopia and retinal diseases necessitates more accessible and efficient eye screening solutions. This study presents a compact, dual-function optical device that integrates fundus photography and refractive error…
Generalist multimodal AI systems such as large language models (LLMs) and vision language models (VLMs) are increasingly accessed by clinicians and patients alike for medical image interpretation through widely available consumer-facing…
Ocular diseases, including diabetic retinopathy and glaucoma, present a significant public health challenge due to their high prevalence and potential for causing vision impairment. Early and accurate diagnosis is crucial for effective…
The rapid advancement of artificial intelligence (AI) in healthcare imaging has revolutionized diagnostic medicine and clinical decision-making processes. This work presents an intelligent multimodal framework for medical image analysis…
Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli, the key functional units of the kidney, from whole slide images (WSIs) in kidney pathology. However, existing open-source tools are…
Objective: To validate and compare the performance of eight available deep learning architectures in grading the severity of glaucoma based on color fundus images. Materials and Methods: We retrospectively collected a dataset of 5978 fundus…
Optical Coherence Tomography (OCT) provides valuable insights in ophthalmology, cardiology, and neurology due to high-resolution, cross-sectional images of the retina. One critical task for ophthalmologists using OCT is delineation of…
Diabetic retinopathy (DR) is a leading cause of blindness worldwide and a common complication of diabetes. As two different imaging tools for DR grading, color fundus photography (CFP) and infrared fundus photography (IFP) are…
Medical image classification is a core task in computer-aided diagnosis (CAD), playing a pivotal role in early disease detection, treatment planning, and patient prognosis assessment. In ophthalmic practice, fluorescein fundus angiography…
The increasing prevalence of retinal diseases poses a significant challenge to the healthcare system, as the demand for ophthalmologists surpasses the available workforce. This imbalance creates a bottleneck in diagnosis and treatment,…
Color fundus image (CFI) bounds detection and contrast enhancement are fundamental tasks in automatic CFI analysis. We present an open-source algorithm, published as a Python package, to automatically extract parametric bounds from color…
Artificial intelligence (AI) has shown great promise in revolutionizing the field of digital health by improving disease diagnosis, treatment, and prevention. This paper describes the Health Guardian platform, a non-commercial, scientific…
Vision impairment and blindness are a major global health challenge where gaps in the ophthalmology workforce limit access to specialist care. We evaluate AMIE, a medically fine-tuned conversational system based on Gemini with integrated…