IEEE transactions on neural networks and learning systems
Feb 6, 2025
Sensory information transmitted to the brain activates neurons to create a series of coping behaviors. Understanding the mechanisms of neural computation and reverse engineering the brain to build intelligent machines requires establishing a robust r...
Feature extraction in ML plays a crucial role in transforming raw data into a more meaningful and interpretable representation. In this study, we thoroughly examined a range of feature extraction techniques and assessed their impact on the binary cla...
Medical & biological engineering & computing
Jan 25, 2025
Accurately classifying optical coherence tomography (OCT) images is essential for diagnosing and treating ophthalmic diseases. This paper introduces a novel generative adversarial network framework called MGR-GAN. The masked image modeling (MIM) meth...
PURPOSE: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can signif...
Biomedical physics & engineering express
Jan 17, 2025
Global blindness is substantially influenced by age-related macular degeneration (AMD). It significantly shortens people's lives and severely impairs their visual acuity. AMD is becoming more common, requiring improved diagnostic and prognostic metho...
BACKGROUND AND OBJECTIVE: Diabetic Retinopathy (DR) is a serious diabetes complication that can cause blindness if not diagnosed in its early stages. Manual diagnosis by ophthalmologists is labor-intensive and time-consuming, particularly in overburd...
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between c...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically grade DR via retinal fundus images (RFIs). However, RFIs a...
Biomedizinische Technik. Biomedical engineering
Jan 6, 2025
OBJECTIVES: Diabetic retinopathy (DR) is associated with long-term diabetes and is a leading cause of blindness if it is not diagnosed early. The rapid growth of deep learning eases the clinicians' DR diagnosing procedure. It automatically extracts t...
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