AIMC Topic: Deep Learning

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Text-Based Emotion Recognition Using Deep Learning Approach.

Computational intelligence and neuroscience
Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions towards a given goal, such as people, activities, organizations, services, subjects, and products. Emotion detection is a subset of sentiment analysis as it predi...

Deep Convolutional Neural Network Mechanism Assessment of COVID-19 Severity.

BioMed research international
As an epidemic, COVID-19's core test instrument still has serious flaws. To improve the present condition, all capabilities and tools available in this field are being used to combat the pandemic. Because of the contagious characteristics of the uniq...

Accurate image-based identification of macroinvertebrate specimens using deep learning-How much training data is needed?

PeerJ
Image-based methods for species identification offer cost-efficient solutions for biomonitoring. This is particularly relevant for invertebrate studies, where bulk samples often represent insurmountable workloads for sorting, identifying, and countin...

Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Accurately diagnosing malignant biliary strictures (MBSs) as benign or malignant remains challenging. It has been suggested that direct visualization and interpretation of cholangioscopy images provide greater accuracy for strict...

Automatic detection of three cell types in a microscope image based on deep learning.

Journal of biophotonics
With the continuous integration of deep learning and the technique of molecular biology, target detection models must accurately detect the position of each cell in the image and classify it correctly. We present a model for the multi-scale feature f...

[Quantitative Evaluation of Airway Lesions in Chronic Obstructive Pulmonary Disease by Applying Deep Learning Reconstruction to Ultra-high-resolution CT Images: Correlation between Wall Area Percentage and Forced Expiratory Volume in One Second Percentage].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: Using ultra-high-resolution images reconstructed with the Advanced intelligent Clear-IQ Engine (AiCE) lung to measure wall area percentage (WA%), we demonstrated that WA% measured in more distal bronchus has a stronger correlation with respi...

Deploying deep learning to estimate the abundance of marine debris from video footage.

Marine pollution bulletin
The insatiable desire of society for plastic goods has led to synthetic materials becoming omnipresent in the marine environment. In attempting to address the problem of plastic pollution, we propose an image classifier based on the YOLOv5 deep learn...

DeepBSA: A deep-learning algorithm improves bulked segregant analysis for dissecting complex traits.

Molecular plant
Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systema...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Scientific reports
Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile...

A lightweight hybrid deep learning system for cardiac valvular disease classification.

Scientific reports
Cardiovascular diseases (CVDs) are a prominent cause of death globally. The introduction of medical big data and Artificial Intelligence (AI) technology encouraged the effort to develop and deploy deep learning models for distinguishing heart sound a...