AIMC Topic: Deep Learning

Clear Filters Showing 27211 to 27220 of 28423 articles

A deep learning approach to dental restoration classification from bitewing and periapical radiographs.

Quintessence international (Berlin, Germany : 1985)
OBJECTIVE: The aim of this study was to examine the success of deep learning-based convolutional neural networks (CNN) in the detection and differentiation of amalgam, composite resin, and metal-ceramic restorations from bitewing and periapical radio...

[Application of deep learning neural network in pathological image classification of non-inflammatory aortic membrane degeneration].

Zhonghua bing li xue za zhi = Chinese journal of pathology
To investigate the value of deep learning in classifying non-inflammatory aortic membrane degeneration. Eighty-nine cases of non-inflammatory aortic media degeneration diagnosed from January to June 2018 were collected at Beijing Anzhen Hospital, C...

A hybrid deep learning model for breast cancer diagnosis based on transfer learning and pulse-coupled neural networks.

Mathematical biosciences and engineering : MBE
Radiology experts often face difficulties in mammography mass lesion labeling, which may lead to conclusive yet unnecessary and expensive breast biopsies. This paper focuses on building an automated diagnosis tool that supports radiologists in identi...

Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images.

Nucleic acids research
Profiling molecular features associated with the morphological landscape of tissue is crucial for investigating the structural and spatial patterns that underlie the biological function of tissues. In this study, we present a new method, spatial gene...

An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners.

The Journal of the Acoustical Society of America
Real-time operation is critical for noise reduction in hearing technology. The essential requirement of real-time operation is causality-that an algorithm does not use future time-frame information and, instead, completes its operation by the end of ...

Robust North Atlantic right whale detection using deep learning models for denoising.

The Journal of the Acoustical Society of America
This paper proposes a robust system for detecting North Atlantic right whales by using deep learning methods to denoise noisy recordings. Passive acoustic recordings of right whale vocalisations are subject to noise contamination from many sources, s...

Macular Ischemia Quantification Using Deep-Learning Denoised Optical Coherence Tomography Angiography in Branch Retinal Vein Occlusion.

Translational vision science & technology
PURPOSE: To examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images.

Journal for immunotherapy of cancer
BACKGROUND: Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) experience a durable clinical benefit (DCB). According to NCCN guidelines, Programmed death-ligand 1 (PD-L1) e...

Classifying Retinal Degeneration in Histological Sections Using Deep Learning.

Translational vision science & technology
PURPOSE: Artificial intelligence (AI) techniques are increasingly being used to classify retinal diseases. In this study we investigated the ability of a convolutional neural network (CNN) in categorizing histological images into different classes of...

Visual Field Inference From Optical Coherence Tomography Using Deep Learning Algorithms: A Comparison Between Devices.

Translational vision science & technology
PURPOSE: To develop a deep learning model to estimate the visual field (VF) from spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) and to compare the performance between them.