Traditional diagnostic methods for Alzheimer’s disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and patient care. Deep convolutional neural networks ...
Classifying medical images is essential in computer-aided diagnosis (CAD). Although the recent success of deep learning in the classification tasks has proven advantages over the traditional feature ...
Using clinical images in DL systems may improve skin cancer detection by providing a more inclusive representation of real-world lesions. DenseNet models outperformed others in binary classification, ...
Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...