AIMC Topic: Deep Learning

Clear Filters Showing 3911 to 3920 of 28423 articles

Semi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation ...

Deep Learning for Classification of Inflammatory Bowel Disease Activity in Whole Slide Images of Colonic Histopathology.

The American journal of pathology
Grading activity of inflammatory bowel disease (IBD) using standardized histopathological scoring systems remains challenging due to limited availability of pathologists with IBD expertise and interobserver variability. In this study, a deep learning...

Cooking loss estimation of semispinalis capitis muscle of pork butt using a deep neural network on hyperspectral data.

Meat science
This study evaluated the performance of a deep-learning-based model that predicted cooking loss in the semispinalis capitis (SC) muscle of pork butts using hyperspectral images captured 24 h postmortem. To overcome low-scale samples, 70 pork butts we...

Multimodal deep-learning model using pre-treatment endoscopic images and clinical information to predict efficacy of neoadjuvant chemotherapy in esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society
BACKGROUND: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, though often ineffective. Therefore, predicting the response to chemotherapy before treatment is desirable. However, there is currently no established m...

Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.

Computers in biology and medicine
Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly increasing due to many factors, such as unhealthy lifestyles, water and food pollution, aging, and medical diagnosis development. Detecting CRC in its e...

Artificial Intelligence for Predicting HER2 Status of Gastric Cancer Based on Whole-Slide Histopathology Images: A Retrospective Multicenter Study.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Human epidermal growth factor receptor 2 (HER2) positive gastric cancer (GC) shows a robust response to the combined therapy based HER2-targeted therapy. The application of these therapies is highly dependent on the evaluation of tumor HER2 status. H...

Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.

European radiology
OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagno...

Development of deep learning auto-encoder algorithms for predicting alcohol use in Korean adolescents based on cross-sectional data.

Social science & medicine (1982)
Alcohol is a highly addictive substance, presenting significant global public health concerns, particularly among adolescents. Previous studies have been limited by traditional research methods, making it challenging to encompass diverse risk factors...

Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.

NeuroImage
RATIONALE AND OBJECTIVES: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently ti...