AIMC Topic: Deep Learning

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Predicting Proteolysis in Complex Proteomes Using Deep Learning.

International journal of molecular sciences
Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins t...

Generalizability of deep learning models for dental image analysis.

Scientific reports
We assessed the generalizability of deep learning models and how to improve it. Our exemplary use-case was the detection of apical lesions on panoramic radiographs. We employed two datasets of panoramic radiographs from two centers, one in Germany (C...

A New Steel Defect Detection Algorithm Based on Deep Learning.

Computational intelligence and neuroscience
In recent years, more and more scholars devoted themselves to the research of the target detection algorithm due to the continuous development of deep learning. Among them, the detection and recognition of small and complex targets are still a proble...

Complementary performances of convolutional and capsule neural networks on classifying microfluidic images of dividing yeast cells.

PloS one
Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. He...

Attend and Guide (AG-Net): A Keypoints-Driven Attention-Based Deep Network for Image Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This article presents a novel keypoints-based attention mechanism for visual recognition in still images. Deep Convolutional Neural Networks (CNNs) for recognizing images with distinctive classes have shown great success, but their performance in dis...

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

Internal and emergency medicine
The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective hospital administration and help to prevent access block. Machine learning (ML) may be able to help with these tasks. For consecutive patients admitte...

Deep learning-based intravascular ultrasound segmentation for the assessment of coronary artery disease.

International journal of cardiology
BACKGROUND: Accurate segmentation of the coronary arteries with intravascular ultrasound (IVUS) is important to optimize coronary stent implantation. Recently, deep learning (DL) methods have been proposed to develop automatic IVUS segmentation. Howe...

Fast and efficient retinal blood vessel segmentation method based on deep learning network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The segmentation of the retinal vascular tree presents a major step for detecting ocular pathologies. The clinical context expects higher segmentation performance with a reduced processing time. For higher accurate segmentation, several automated met...

Deep learning based segmentation of brain tissue from diffusion MRI.

NeuroImage
Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weigh...