AIMC Topic: Deep Learning

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Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning.

Scientific reports
Auscultation has been essential part of the physical examination; this is non-invasive, real-time, and very informative. Detection of abnormal respiratory sounds with a stethoscope is important in diagnosing respiratory diseases and providing first a...

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.

Nature communications
Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable transition of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have great ...

Exploring palatal and dental shape variation with 3D shape analysis and geometric deep learning.

Orthodontics & craniofacial research
OBJECTIVES: Palatal shape contains a lot of information that is of clinical interest. Moreover, palatal shape analysis can be used to guide or evaluate orthodontic treatments. A statistical shape model (SSM) is a tool that, by means of dimensionality...

On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays.

Sensors (Basel, Switzerland)
The global COVID-19 pandemic that started in 2019 and created major disruptions around the world demonstrated the imperative need for quick, inexpensive, accessible and reliable diagnostic methods that would allow the detection of infected individual...

Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks.

Sensors (Basel, Switzerland)
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Au...

Comparing recurrent convolutional neural networks for large scale bird species classification.

Scientific reports
We present a deep learning approach towards the large-scale prediction and analysis of bird acoustics from 100 different bird species. We use spectrograms constructed on bird audio recordings from the Cornell Bird Challenge (CBC)2020 dataset, which i...

PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions.

BMC bioinformatics
BACKGROUND: Plant long non-coding RNAs (lncRNAs) play vital roles in many biological processes mainly through interactions with RNA-binding protein (RBP). To understand the function of lncRNAs, a fundamental method is to identify which types of prote...

Deep Learning-Based Image Automatic Assessment and Nursing of Upper Limb Motor Function in Stroke Patients.

Journal of healthcare engineering
This paper mainly introduces the relevant contents of automatic assessment of upper limb mobility after stroke, including the relevant knowledge of clinical assessment of upper limb mobility, Kinect sensor to realize spatial location tracking of uppe...

Research on Classification of COVID-19 Chest X-Ray Image Modal Feature Fusion Based on Deep Learning.

Journal of healthcare engineering
Most detection methods of coronavirus disease 2019 (COVID-19) use classic image classification models, which have problems of low recognition accuracy and inaccurate capture of modal features when detecting chest X-rays of COVID-19. This study propos...

Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image segmentation quality is the main metric that is often considered with memory and computation effici...