8 天前 - … The advancements in DL, particularly through the use of convolutional neural networks
(… in the detection, classification, and segmentation of prostate cancer, establishing their …

8 天前 - … is the exploration of deep learning, particularly convolutional neural networks (CNNs), …
of prostate cancer characterization. The model employs a patch-based approach, …

8 天前 - … of deep learning, particularly convolutional neural networks (… the precision of
prostate cancer characterization. The … Image Computing and Computer Assisted Intervention (…

10 天前 - … and convolutional neural networks for prostate cancer metabolomics data classification.
… Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease…

31 天前 - … The essence of our DL approach in this study is rooted in the adoption of a multiconvolutional
neural network (multi-CNN) model, which is a critical element of our methodology …

48 天前 - … neural network models for PCa detection. To improve robustness to out-of-distribution …
Our deep learning model consists of a feature extractor \(f_\theta (\cdot )\) which maps an …

53 天前 - … and bulk transcriptome-based diagnostic assessment model. First… genes and deep
learning methods. The Linear … of machine learning and convolutional neural networks for the …

65 天前 - … This research explores using deep learning models for automatic feature extraction
… prostate cancer lesion binary semantic segmentation using convolutional neural networks. …

67 天前 - … of tumor areas was created based on pathologist-annotated regions … A deep
convolutional GAN was created from scratch to … evaluation using a convolutional neural network …

67 天前 - … deep learning framework that utilizes biomarkers from both MRI and TRUS images
during training to detect prostate cancer … a multimodal deep neural network that learns from …