Deep learning is a branch of artificial intelligence. In recent years, with the advantages of
automatic learning and feature extraction, it has been widely concerned by academic and …

Data-driven approaches have great potential to shape future practices in radiology. The
most straightforward strategy to obtain clinically accurate models is to use large, well …

Prompt plant disease detection is critical to prevent plagues and to mitigate their effects on
crops. The most accurate automatic algorithms for plant disease identification using plant …

Rotating machinery intelligent diagnosis with large data has been researched
comprehensively, while there is still a gap between the existing diagnostic model and the …

In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by
limitations in data collection and in model transparency and interpretability. Here we …

In computer vision, particularly in label categorization, attributing features such as color,
shape, and tissue size to each category presents a formidable challenge. Dense features …

Cell-line screens create expansive datasets for learning predictive markers of drug
response, but these models do not readily translate to the clinic with its diverse contexts and …

Many known supervised deep learning methods for medical image segmentation suffer an
expensive burden of data annotation for model training. Recently, few-shot segmentation …

Colorectal cancer has a great incidence rate worldwide, but its early detection significantly
increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and …

Agriculture is the ultimate imperative and primary source of origin to furnish domestic income
for multifarious countries. The disease caused in plants due to various pathogens like …