AIMC Topic: Deep Learning

Clear Filters Showing 15351 to 15360 of 28423 articles

Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework.

Interdisciplinary sciences, computational life sciences
Atypical visual attention is a hallmark of autism spectrum disorder (ASD). Identifying the attention features accurately discerning between people with ASD and typically developing (TD) at the individual level remains a challenge. In this study, we d...

Development and Validation of a Visually Explainable Deep Learning Model for Classification of C-shaped Canals of the Mandibular Second Molars in Periapical and Panoramic Dental Radiographs.

Journal of endodontics
INTRODUCTION: The purpose of this study was to develop and validate a visually explainable deep learning model for the classification of C-shaped canals of the mandibular second molars in dental radiographs.

Pseudo low-energy monochromatic imaging of head and neck cancers: Deep learning image reconstruction with dual-energy CT.

International journal of computer assisted radiology and surgery
PURPOSE: Low-energy virtual monochromatic images (VMIs) derived from dual-energy computed tomography (DECT) systems improve lesion conspicuity of head and neck cancer over single-energy CT (SECT). However, DECT systems are installed in a limited numb...

Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.

Annals of biomedical engineering
Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which first appeared in Wuhan, China, and has since spread in the whole world. This pathology has caused a ma...

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.

Radiology
Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed with multimodal US. Purpose To develop DL algorithms for the automated classification of benign versus malignant ovarian tumors assessed with US and ...

A deep learning-based system for assessment of serum quality using sample images.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Serum quality is an important factor in the pre-analytical phase of laboratory analysis. Visual inspection of serum quality (including recognition of hemolysis, icterus, and lipemia) is widely used in clinical laboratories but is time-con...

TransPhos: A Deep-Learning Model for General Phosphorylation Site Prediction Based on Transformer-Encoder Architecture.

International journal of molecular sciences
Protein phosphorylation is one of the most critical post-translational modifications of proteins in eukaryotes, which is essential for a variety of biological processes. Plenty of attempts have been made to improve the performance of computational pr...

A weakly supervised deep learning-based method for glioma subtype classification using WSI and mpMRIs.

Scientific reports
Accurate glioma subtype classification is critical for the treatment management of patients with brain tumors. Developing an automatically computer-aided algorithm for glioma subtype classification is challenging due to many factors. One of the diffi...

Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates.

Scientific reports
Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radio...

Large-Scale Textual Datasets and Deep Learning for the Prediction of Depressed Symptoms.

Computational intelligence and neuroscience
Millions of people worldwide suffer from depression. Assessing, treating, and preventing recurrence requires early detection of depressive symptoms as depression-related datasets expand and machine learning improves, intelligent approaches to detect ...