AIMC Topic: Deep Learning

Clear Filters Showing 11201 to 11210 of 28423 articles

Design of Nurr1 Agonists Fragment-Augmented Generative Deep Learning in Low-Data Regime.

Journal of medicinal chemistry
Generative neural networks trained on SMILES can design innovative bioactive molecules . These so-called chemical language models (CLMs) have typically been trained on tens of template molecules for fine-tuning. However, it is challenging to apply CL...

Handwriting Evaluation Using Deep Learning with SensoGrip.

Sensors (Basel, Switzerland)
Handwriting learning disabilities, such as dysgraphia, have a serious negative impact on children's academic results, daily life and overall well-being. Early detection of dysgraphia facilitates an early start of targeted intervention. Several studie...

Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms.

BMC medical research methodology
OBJECTIVE: PONV reduces patient satisfaction and increases hospital costs as patients remain in the hospital for longer durations. In this study, we build a preliminary artificial intelligence algorithm model to predict early PONV in patients.

Ensemble-based multi-tissue classification approach of colorectal cancer histology images using a novel hybrid deep learning framework.

Scientific reports
Colorectal cancer (CRC) is the second leading cause of cancer death in the world, so digital pathology is essential for assessing prognosis. Due to the increasing resolution and quantity of whole slide images (WSIs), as well as the lack of annotated ...

Ultrasound guidance in navigated liver surgery: toward deep-learning enhanced compensation of deformation and organ motion.

International journal of computer assisted radiology and surgery
PURPOSE: Accuracy of image-guided liver surgery is challenged by deformation of the liver during the procedure. This study aims at improving navigation accuracy by using intraoperative deep learning segmentation and nonrigid registration of hepatic v...

DC-cycleGAN: Bidirectional CT-to-MR synthesis from unpaired data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Magnetic resonance (MR) and computer tomography (CT) images are two typical types of medical images that provide mutually-complementary information for accurate clinical diagnosis and treatment. However, obtaining both images may be limited due to so...

Deep learning algorithm for predicting subacromial motion trajectory: Dynamic shoulder ultrasound analysis.

Ultrasonics
Subacromial motion metrics can be extracted from dynamic shoulder ultrasonography, which is useful for identifying abnormal motion patterns in painful shoulders. However, frame-by-frame manual labeling of anatomical landmarks in ultrasound images is ...

The Deep Learning Generative Adversarial Random Neural Network in data marketplaces: The digital creative.

Neural networks : the official journal of the International Neural Network Society
Generative Adversarial Networks (GANs) have been proposed as a method to generate multiple replicas from an original version combining a Discriminator and a Generator. The main applications of GANs have been the casual generation of audio and video c...

HAL-IA: A Hybrid Active Learning framework using Interactive Annotation for medical image segmentation.

Medical image analysis
High performance of deep learning models on medical image segmentation greatly relies on large amount of pixel-wise annotated data, yet annotations are costly to collect. How to obtain high accuracy segmentation labels of medical images with limited ...