Latest AI and machine learning research in laser surgery for healthcare professionals.
Occlusion and the scarcity of labeled surgical data are significant challenges in disparity estimation for stereo laparoscopic images. To address these issues, this study proposes a Depth Guided Occlusion-Aware Disparity Refinement Network (DGORNet), which refines disparity maps by leveraging monocular depth information unaffected by occlusion. A Position Embedding (PE) module is introduced to p...
Rhegmatogenous retinal detachment (RRD) is a serious ophthalmic condition that, if untreated, can result in significant vision loss. Proliferative vitreoretinopathy (PVR) often complicates RRD and is the leading cause of surgical failure. Proteomic analysis of the vitreous has emerged as a powerful tool for elucidating the molecular mechanisms underlying RRD and PVR. This article reviews proteomic...
Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered ...
BACKGROUND: This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first i...
In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophtha...
The adoption of standardized imaging protocols in retinal imaging is critical to overcoming challenges posed by fragmented data formats across devices...
Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary...
Self-supervised learning (SSL) has enabled Vision Transformers (ViTs) to learn robust representations from large-scale natural image datasets, enhan...
The safety and efficacy of irreversible electroporation (IRE) in tumor therapy has been validated over many years by clinical application. An in-depth...
The Hillel Yaffe Age Related Macular Degeneration (HYAMD) dataset is a longitudinal collection of 1,560 Digital Fundus Images (DFIs) from 325 patien...
High-quality fundus images provide essential anatomical information for clinical screening and ophthalmic disease diagnosis. Yet, due to hardware li...
Ophthalmic diseases pose a significant global health challenge, yet traditional diagnosis methods and existing single-eye deep learning approaches o...
Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied acro...
Medical Large Vision-Language Models (Med-LVLMs) demonstrate significant potential in healthcare, but their reliance on general medical data and coa...
Soft robots exhibit inherent compliance and safety, which makes them particularly suitable for applications requiring direct physical interaction wi...
Accurate retinal vessel segmentation provides essential structural information for ophthalmic image analysis. However, existing methods struggle wit...
The growing burden of myopia and retinal diseases necessitates more accessible and efficient eye screening solutions. This study presents a compact,...
Accurate measurement of eyelid parameters such as Margin Reflex Distances (MRD1, MRD2) and Levator Function (LF) is critical in oculoplastic diagnos...
With the advancements in medical artificial intelligence (AI), fundus image classifiers are increasingly being applied to assist in ophthalmic diagn...
Large language models (LLMs) are increasingly used in healthcare, but their reliability is heavily influenced by user-driven factors such as questio...