Image fusion is a challenging task that aims to generate a composite image by combining information from diverse sources. While deep learning (DL) algorithms have achieved promising results, most rely on complex encoders or attention mechanisms, lead...
BACKGROUND: The pathological and physiological state of patients with intracerebral hemorrhage (ICH) after minimally invasive surgery (MIS) is a dynamic evolution, and the traditional models cannot dynamically predict prognosis. Clinical data at mult...
Cardiovascular disease (CVD) causes severe global health threat, and electrocardiogram (ECG) is crucial for early CVD diagnosis. Recently, two popular deep learning methods, that is, convolutional neural network (CNN) and long short-term memory (LSTM...
Proteases, enzymes that play critical roles in health and disease, exert their function through the cleavage of peptide bonds. Identifying substrates that are efficiently and selectively cleaved by target proteases is essential for studying protease ...
YTHDC2, a unique YTH-domain-containing protein that recognizes N6-methyladenosine (mA) on RNA, plays critical roles in diverse pathological processes and represents a promising therapeutic target. Despite its potential, no potent small-molecule inhib...
BACKGROUND: Accurate classification and grading of lymphoma subtypes are essential for treatment planning. Traditional diagnostic methods face challenges of subjectivity and inefficiency, highlighting the need for automated solutions based on deep le...
BACKGROUND: Keratoconus (KCN) is a progressive degenerative corneal disorder characterized by corneal thinning and cone-shaped protrusion, leading to significant visual impairment if not detected early. Accurate staging of KCN using corneal topograph...
Biomedical physics & engineering express
Jan 6, 2026
. Accurate detection and segmentation of brain metastases (BM) from MRI are critical for the appropriate management of cancer patients. This study investigates strategies to enhance the robustness of artificial intelligence (AI)-based BM detection an...
Diabetic Retinopathy, Cataract, and Glaucoma are major retinal diseases that require early detection to prevent irreversible vision loss. This study proposes a deep learning-based framework for the automated classification of retinal images into four...
Robotic surgery has emerged as a key minimally invasive approach for gastrointestinal malignancies, stimulating substantial global research activity. This study employed bibliometric and visual methods to map the knowledge structure, evolutionary tra...
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