AIMC Topic: Deep Learning

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Bacterial colony size growth estimation by deep learning.

BMC microbiology
The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide important data from a medical and veterinary point of view. We trained convolutional neural networks (CNNs) ...

Reconstruction of shoulder MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

European radiology experimental
BACKGROUND: To investigate the potential of combining compressed sensing (CS) and deep learning (DL) for accelerated two-dimensional (2D) and three-dimensional (3D) magnetic resonance imaging (MRI) of the shoulder.

Convolutional neural network model by deep learning and teaching robot in keyboard musical instrument teaching.

PloS one
Keyboard instruments play a significant role in the music teaching process, providing students with an enjoyable musical experience while enhancing their music literacy. This study aims to investigate the current state of keyboard instrument teaching...

Shear wave elastography-based deep learning model for prognosis of patients with acutely decompensated cirrhosis.

Journal of clinical ultrasound : JCU
PURPOSE: This study aimed to develop and validate a deep learning model based on two-dimensional (2D) shear wave elastography (SWE) for predicting prognosis in patients with acutely decompensated cirrhosis.

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability.

Deep learning methods for blood flow reconstruction in a vessel with contrast enhanced x-ray computed tomography.

International journal for numerical methods in biomedical engineering
The reconstruction of blood velocity in a vessel from contrast enhanced x-ray computed tomography projections is a complex inverse problem. It can be formulated as reconstruction problem with a partial differential equation constraint. A solution can...

[Physical Properties of Small Focal Spot Imaging with Deep Learning Reconstruction in Chest-abdominal Plain CT].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The aim of this study was to compare the physical properties of small focal spot imaging with deep learning reconstruction (DLR) and small or large focal spot imaging with hybrid iterative reconstruction (IR) in chest-abdominal plain compute...

Automatic detection and differential diagnosis of age-related macular degeneration from color fundus photographs using deep learning with hierarchical vision transformer.

Computers in biology and medicine
Age-related macular degeneration (AMD) is a leading cause of vision loss in the elderly, highlighting the need for early and accurate detection. In this study, we proposed DeepDrAMD, a hierarchical vision transformer-based deep learning model that in...

The performance of deep learning on thyroid nodule imaging predicts thyroid cancer: A systematic review and meta-analysis of epidemiological studies with independent external test sets.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: It is still controversial whether deep learning (DL) systems add accuracy to thyroid nodule imaging classification based on the recent available evidence. We conducted this study to analyze the current evidence of DL in thyroid n...

PortPred: Exploiting deep learning embeddings of amino acid sequences for the identification of transporter proteins and their substrates.

Journal of cellular biochemistry
The physiology of every living cell is regulated at some level by transporter proteins which constitute a relevant portion of membrane-bound proteins and are involved in the movement of ions, small and macromolecules across bio-membranes. The importa...