Deep learning-based fundus image enhancement has attracted extensive research attention recently, which has shown remarkable effectiveness in improving the visibility of low-quality images. However, these methods are often constrained to specific dat...
Ribonucleic acid (RNA) structural motif identification is a crucial step for understanding RNA structure and functionality. Due to the complexity and variations of RNA 3D structures, identifying RNA structural motifs is challenging and time-consuming...
BACKGROUND: India is home to about 42 million people with β-thalassemia trait (βTT) necessitating screening of βTT to stop spread of the disease. Over the years, researchers developed discrimination formulae based on red blood cell (RBC) parameters t...
Correct identification of blood-sucking bugs, such as triatomines, is important because they are vectors of Chagas' disease. Identifying these insects is often difficult for non-specialists. Deep learning is emerging as a solution for automated ident...
White blood cell (WBC) detection is pivotal in medical diagnostics, crucial for diagnosing infections, inflammations, and certain cancers. Traditional WBC detection methods are labor-intensive and time-consuming. Convolutional Neural Networks (CNNs) ...
Neuroblastoma presents a wide variety of clinical phenotypes, demonstrating different levels of benignity and malignancy among its subtypes. Early diagnosis is essential for effective patient management. Computed tomography (CT) serves as a significa...
Journal of computer-aided molecular design
Apr 26, 2025
Predicting molecular toxicity is an important stage in the process of drug discovery. It is directly related to medical destiny and human health. This paper presents an enhanced model for chemical respiratory toxicity prediction. It used a combinatio...
Interdisciplinary sciences, computational life sciences
Apr 25, 2025
With the development of single-cell RNA-sequencing (scRNA-seq) technology, scRNA-seq data analysis suffers huge challenges due to large scale, high dimensionality, high noise, and high sparsity. To achieve accurately embedded representation in the la...
PURPOSE: To provide a perspective on the feasibility and utility of automating image segmentation with artificial intelligence (AI)-based deep-learning algorithms to quantify retinoschisis cystic cavity volume in patients with X-linked retinoschisis ...
Neural networks : the official journal of the International Neural Network Society
Apr 25, 2025
Deep Reinforcement Learning (DRL) has attracted the interest of researchers due to its ability to provide valuable solutions to a variety of problems in different fields, such as robotics, autonomous driving, financial trading, and more. However, DRL...
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