AIMC Topic: Deep Learning

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Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

Scientific reports
The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk fact...

Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images.

Nature communications
With age, the prevalence of diseases such as fatty liver disease, cirrhosis, and type two diabetes increases. Approaches to both predict abdominal age and identify risk factors for accelerated abdominal age may ultimately lead to advances that will d...

Nucleosome positioning based on DNA sequence embedding and deep learning.

BMC genomics
BACKGROUND: Nucleosome positioning is the precise determination of the location of nucleosomes on DNA sequence. With the continuous advancement of biotechnology and computer technology, biological data is showing explosive growth. It is of practical ...

Optimization-Based Ensemble Feature Selection Algorithm and Deep Learning Classifier for Parkinson's Disease.

Journal of healthcare engineering
PD (Parkinson's Disease) is a severe malady that is painful and incurable, affecting older human beings. Identifying PD early in a precise manner is critical for the lengthened survival of patients, where DMTs (data mining techniques) and MLTs (machi...

Prediction of Hearing Prognosis of Large Vestibular Aqueduct Syndrome Based on the PyTorch Deep Learning Model.

Journal of healthcare engineering
In order to compare magnetic resonance imaging (MRI) findings of patients with large vestibular aqueduct syndrome (LVAS) in the stable hearing loss (HL) group and the fluctuating HL group, this paper provides reference for clinicians' early intervent...

Effectiveness of English Online Learning Based on Deep Learning.

Computational intelligence and neuroscience
With the popularization of the Internet lifestyle and the innovation of learning methods, more and more online learning systems have emerged, allowing users to study in the system anytime and anywhere. While providing convenience to users, online lea...

Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models.

Computational intelligence and neuroscience
Spondylolisthesis refers to the slippage of one vertebral body over the adjacent one. It is a chronic condition that requires early detection to prevent unpleasant surgery. The paper presents an optimized deep learning model for detecting spondylolis...

Happy work: Improving enterprise human resource management by predicting workers' stress using deep learning.

PloS one
Recently, workers in most enterprises suffer from excessive occupational stress in the workplace, which negatively affects workers' productivity, safety, and health. To deal with stress in workers, it is vital for the human resource management (HRM) ...

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

PloS one
BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early prevention and better government strategic planning. In this paper, we presented different prediction models using deep learning methods based on the month...

Automatic diagnosis and grading of patellofemoral osteoarthritis from the axial radiographic view: a deep learning-based approach.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Patellofemoral osteoarthritis (PFOA) has a high prevalence and is assessed on axial radiography of the patellofemoral joint (PFJ). A deep learning (DL)-based approach could help radiologists automatically diagnose and grade PFOA via inter...