AIMC Topic: Deep Learning

Clear Filters Showing 6481 to 6490 of 28423 articles

Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.

European radiology
OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enhanced ultrasound (CEUS) to predict vessels encapsulating tumor clusters (VETC) patterns in hepatocellular carcinoma (HCC).

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

European radiology
OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary...

Photonic deep residual time-delay reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Time-delay reservoir computing (TDRC) represents a simplified variant of recurrent neural networks, employing a nonlinear node with a feedback mechanism to construct virtual nodes. The capabilities of TDRC can be enhanced by transitioning to a deep a...

Textual emotion classification using MPNet and cascading broad learning.

Neural networks : the official journal of the International Neural Network Society
As one of the most important tasks of natural language processing, textual emotion classification (TEC) aims to recognize and detect all emotions contained in texts. However, most existing methods are implemented using deep learning approaches, which...

AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs.

Bone
Despite well-defined criteria for radiographic diagnosis of atypical femur fractures (AFFs), missed and delayed diagnosis is common. An AFF diagnostic software could provide timely AFF detection to prevent progression of incomplete or development of ...

Efficient application of deep learning-based elective lymph node regions delineation for pelvic malignancies.

Medical physics
BACKGROUND: While there are established international consensuses on the delineation of pelvic lymph node regions (LNRs), significant inter- and intra-observer variabilities persist. Contouring these clinical target volumes for irradiation in pelvic ...

Using deep learning for predicting the dynamic evolution of breast cancer migration.

Computers in biology and medicine
BACKGROUND: Breast cancer (BC) remains a prevalent health concern, with metastasis as the main driver of mortality. A detailed understanding of metastatic processes, particularly cell migration, is fundamental to improve therapeutic strategies. The w...

Elucidating Microglial Heterogeneity and Functions in Alzheimer's Disease Using Single-cell Analysis and Convolutional Neural Network Disease Model Construction.

Scientific reports
In this study, we conducted an in-depth exploration of Alzheimer's Disease (AD) by integrating state-of-the-art methodologies, including single-cell RNA sequencing (scRNA-seq), weighted gene co-expression network analysis (WGCNA), and a convolutional...

Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model.

International dental journal
OBJECTIVES: Several factors such as unavailability of specialists, dental phobia, and financial difficulties may lead to a delay between receiving an oral radiology report and consulting a dentist. The primary aim of this study was to distinguish bet...