AIMC Topic: Deep Learning

Clear Filters Showing 10211 to 10220 of 28423 articles

Developing a Continuous Severity Scale for Macular Telangiectasia Type 2 Using Deep Learning and Implications for Disease Grading.

Ophthalmology
PURPOSE: Deep learning (DL) models have achieved state-of-the-art medical diagnosis classification accuracy. Current models are limited by discrete diagnosis labels, but could yield more information with diagnosis in a continuous scale. We developed ...

Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models coul...

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

International orthopaedics
PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning w...

Protocol to analyze fundus images for multidimensional quality grading and real-time guidance using deep learning techniques.

STAR protocols
Data quality issues have been acknowledged as one of the greatest obstacles in medical artificial intelligence research. Here, we present DeepFundus, which employs deep learning techniques to perform multidimensional classification of fundus image qu...

Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network.

The American journal of pathology
The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs o...

Evaluation of a newly designed deep learning-based algorithm for automated assessment of scapholunate distance in wrist radiography as a surrogate parameter for scapholunate ligament rupture and the correlation with arthroscopy.

La Radiologia medica
PURPOSE: Not diagnosed or mistreated scapholunate ligament (SL) tears represent a frequent cause of degenerative wrist arthritis. A newly developed deep learning (DL)-based automated assessment of the SL distance on radiographs may support clinicians...

Cross-domain mechanism for few-shot object detection on Urine Sediment Image.

Computers in biology and medicine
Deep learning object detection networks require a large amount of box annotation data for training, which is difficult to obtain in the medical image field. The few-shot object detection algorithm is significant for an unseen category, which can be i...

ReactionDataExtractor 2.0: A Deep Learning Approach for Data Extraction from Chemical Reaction Schemes.

Journal of chemical information and modeling
Knowledge in the chemical domain is often disseminated graphically via chemical reaction schemes. The task of describing chemical transformations is greatly simplified by introducing reaction schemes that are composed of chemical diagrams and symbols...

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Artificial intelligence in medicine
Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are prone to...

Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models.

Journal of neural engineering
Development of brain-computer interface (BCI) technology is key for enabling communication in individuals who have lost the faculty of speech due to severe motor paralysis. A BCI control strategy that is gaining attention employs speech decoding from...