AIMC Topic: Humans

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Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities.

Computational and mathematical methods in medicine
Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT) is a mathematical process that generates images at many different angles around the patient. Image reconstruction has a fundamental impact on image quality. In rece...

Deep Learning-Based CT Imaging for the Diagnosis of Liver Tumor.

Computational intelligence and neuroscience
The objective of this research was to investigate the application value of deep learning-based computed tomography (CT) images in the diagnosis of liver tumors. Fifty-eight patients with liver tumors were selected, and their CT images were segmented ...

Improved Analysis of COVID-19 Influenced Pneumonia from the Chest X-Rays Using Fine-Tuned Residual Networks.

Computational intelligence and neuroscience
COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become more contagious. If such a situation occurs, the resulting calamity will be worse than in the past if...

Impact of the suboptimal communication network environment on telerobotic surgery performance and surgeon fatigue.

PloS one
BACKGROUND: Remote surgery social implementation necessitates achieving low latency and highly reliable video/operation signal transmission over economical commercial networks. However, with commercial lines, communication bandwidth often fluctuates ...

The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: The coronavirus disease 2019 (COVID-19) has caused a crisis worldwide. Amounts of efforts have been made to prevent and control COVID-19's transmission, from early screenings to vaccinations and treatments. Recently, due to the spring up ...

Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.

European radiology
OBJECTIVES: Artificial intelligence (AI) has shown promising results when used on retrospective data from mammographic screening. However, few studies have explored the possible consequences of different strategies for combining AI and radiologists i...

Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study.

AJR. American journal of roentgenology
Deep learning-based convolutional neural networks have enabled major advances in development of artificial intelligence (AI) software applications. Modern AI applications offer comprehensive multiorgan evaluation. The purpose of this article was to...

[Early mobilization in the intensive care unit-Are robot-assisted systems the future?].

Die Anaesthesiologie
BACKGROUND: Intensive care unit (ICU) acquired weakness is associated with reduced physical function, increased mortality and reduced quality of life, and affects about 43% of survivors of critical illness. Lacking therapeutic options, the prevention...

Motion correction for native myocardial T mapping using self-supervised deep learning registration with contrast separation.

NMR in biomedicine
In myocardial T mapping, undesirable motion poses significant challenges because uncorrected motion can affect T estimation accuracy and cause incorrect diagnosis. In this study, we propose and evaluate a motion correction method for myocardial T map...

Deep learning-based reconstruction of virtual monoenergetic images of kVp-switching dual energy CT for evaluation of hypervascular liver lesions: Comparison with standard reconstruction technique.

European journal of radiology
OBJECTIVE: To investigate clinical applicability of deep learning(DL)-based reconstruction of virtual monoenergetic images(VMIs) of arterial phase liver CT obtained by rapid kVp-switching dual-energy CT for evaluation of hypervascular liver lesions.