AIMC Topic: Deep Learning

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Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

Hepatology international
BACKGROUND AND AIMS: Chronic hepatitis B virus (CHB) infection remains a major global health burden and the non-invasive and accurate diagnosis of significant liver fibrosis (≥ F2) in CHB patients is clinically very important. This study aimed to ass...

Deep Learning-Assisted Automated Single Cell Electroporation Platform for Effective Genetic Manipulation of Hard-to-Transfect Cells.

Small (Weinheim an der Bergstrasse, Germany)
Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms of disease. A critical step in many such studies is the intracellular delivery of the gene editing ma...

n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications.

Sensors (Basel, Switzerland)
This paper provides a conceptual foundation for stochastic duels and contains a further study of the game models based on the theory of stochastic duels. Some other combat assessment techniques are looked upon briefly; a modern outlook on the applica...

Method to Minimize the Errors of AI: Quantifying and Exploiting Uncertainty of Deep Learning in Brain Tumor Segmentation.

Sensors (Basel, Switzerland)
Despite the unprecedented success of deep learning in various fields, it has been recognized that clinical diagnosis requires extra caution when applying recent deep learning techniques because false prediction can result in severe consequences. In t...

An end-to-end computer vision methodology for quantitative metallography.

Scientific reports
Metallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the occurrence and characteristics of inclusions or precipitates. This work presents a holistic few-shot ...

EDNC: Ensemble Deep Neural Network for COVID-19 Recognition.

Tomography (Ann Arbor, Mich.)
The automatic recognition of COVID-19 diseases is critical in the present pandemic since it relieves healthcare staff of the burden of screening for infection with COVID-19. Previous studies have proven that deep learning algorithms can be utilized t...

Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies.

Nature medicine
Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation of EMBs is affected by substantial interobserver and intraobserver variability, which often leads t...

Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm-Based MRI Information.

Contrast media & molecular imaging
This study was aimed to explore the application of cardiac magnetic resonance imaging (MRI) image segmentation model based on U-Net in the diagnosis of a valvular heart disease. The effect of continuous nursing on the survival of discharged patients ...

Computational bioacoustics with deep learning: a review and roadmap.

PeerJ
Animal vocalisations and natural soundscapes are fascinating objects of study, and contain valuable evidence about animal behaviours, populations and ecosystems. They are studied in bioacoustics and ecoacoustics, with signal processing and analysis a...

Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

Contrast media & molecular imaging
This study was aimed at exploring the application of image segmentation based on full convolutional neural network (FCN) in liver computed tomography (CT) image segmentation and analyzing the clinical features of acute liver injury caused by sepsis. ...