BACKGROUND: Predicting drug-target interactions (DTIs) is essential for accelerating drug discovery, yet traditional experimental methods are time-consuming and costly. Computational approaches, especially those using machine learning and deep learni...
The classification of human skin disorders, particularly benign and malignant skin cancer, is thoroughly examined in this study with a focus on protecting data privacy. Traditional visual diagnosis of skin disorders is often subjective and complicate...
Renal cell carcinomas (RCCs) are the seventh most widespread histological cancer. Around 40% of patients die in RCC due to the disease development. Thus, this tumour is the most lethal malignant urological tumour. The histopathologic classification o...
Detecting and segmenting brain tumors from 3D MRI images is a challenging and time-intensive task for clinicians. This research introduces an innovative hybrid architecture for deep learning, comprising a 3D fully convolutional neural network (3D-FCN...
Globalization is claimed to have a homogenizing effect, reducing pronounced local cultural differences. Indoor living spaces are among the most vivid expressions of local culture, yet they remain underexplored in this context. Our visual AI framework...
Deep learning models show promise in accelerating the design and optimization of antimicrobial peptides (AMPs), but current methods face challenges, such as low success rates, or large virtual library scales. In this study, we introduce DLFea4AMPGen,...
Environmental monitoring and assessment
Oct 15, 2025
Groundwater salinization poses a critical threat to freshwater security in coastal regions, particularly under intensified extraction and evolving hydroclimatic conditions. This study examines the spatial and temporal evolution of salinity in the low...
3D conventional photoacoustic (PA) imaging often suffers from visibility artifacts caused by the limited bandwidth and constrained viewing angles of ultrasound transducers, as well as the use of sparse arrays. PA fluctuation imaging (PAFI), which lev...
Rapid and accurate quantitative assessment of muscle tissue characteristics is valuable for the diagnosis and monitoring of neuromuscular diseases (NMDs). Quantitative magnetic resonance imaging (MRI) enables non-invasive assessment of muscle patholo...
. Deep learning has emerged as a powerful approach for decoding electroencephalography (EEG)-based brain-computer interface (BCI) signals. However, its effectiveness is often limited by the scarcity and variability of available training data. Existin...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.