Invention Description Multimodal large language models (MLLMs) have shown strong potential in analyzing complex data types such as images, video, and audio, prompting growing interest in their use for medical applications. While several general-domain MLLMs have been adapted for healthcare tasks, including retinal imaging, their performance remains...

The rise of artificial intelligence is changing the shape of many different fields, and ophthalmic medicine is no exception. Convolutional neural networks (CNNs) have achieved remarkable results in the assisted diagnosis of ophthalmic diseases. However, they face challenges such as limited labeling and small dataset sizes. In recent years, self-supervised...

Background In the rapid evolution of deep learning, neural network models have been growing from several to over a hundred layers for handling more complex tasks. Network models are often trained with powerful GPUs in the cloud or on stand-alone servers, and the trained models are then deployed to certain hardware platforms for performing inference....