AIMC Topic: Deep Learning

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Deep Learning Using Electrocardiograms in Patients on Maintenance Dialysis.

Advances in kidney disease and health
Cardiovascular morbidity and mortality occur with an extraordinarily high incidence in the hemodialysis-dependent end-stage kidney disease population. There is a clear need to improve identification of those individuals at the highest risk of cardiov...

Deep Learning Based on Enhanced MRI T1 Imaging to Differentiate Small-cell and Non-small-cell Primary Lung Cancers in Patients with Brain Metastases.

Current medical imaging
OBJECTIVES: To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) for patients with brain metastases (BMs) based on a deep learning (DL) model using contrast-enhanced magnetic resonance imaging (MRI) T1 wei...

Research on Segmentation Technology in Lung Cancer Radiotherapy Based on Deep Learning.

Current medical imaging
BACKGROUND: Lung cancer has the highest mortality rate among cancers. Radiation therapy (RT) is one of the most effective therapies for lung cancer. The correct segmentation of lung tumors (LTs) and organs at risk (OARs) is the cornerstone of success...

Finding Hierarchical Structure in Binary Sequences: Evidence from Lindenmayer Grammar Learning.

Cognitive science
In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher-order regularities of a highly simplified input where only sequential-order infor...

HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures.

Bioinformatics (Oxford, England)
MOTIVATION: Protein and peptide engineering has become an essential field in biomedicine with therapeutics, diagnostics and synthetic biology applications. Helices are both abundant structural feature in proteins and comprise a major portion of bioac...

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

Journal of Parkinson's disease
BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagnosis of IPD. Cardiac autonomic dysfunction begins in the early stages of IPD, and an electrocardiogr...

Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Non-invasive Brain-Computer Interface (BCI) uses an electroencephalogram (EEG) to obtain information on brain neural activity. Because EEG can be contaminated by various artifacts during the collection process, it has primarily evolved in...

Image restoration for blurry optical images caused by photon diffusion with deep learning.

Journal of the Optical Society of America. A, Optics, image science, and vision
Optical macroscopic imaging techniques have shown great significance in the investigations of biomedical issues by revealing structural or functional information of living bodies through the detection of visible or near-infrared light derived from di...

Segmentation of Clinical Target Volume From CT Images for Cervical Cancer Using Deep Learning.

Technology in cancer research & treatment
Segmentation of clinical target volume (CTV) from CT images is critical for cervical cancer brachytherapy, but this task is time-consuming, laborious, and not reproducible. In this work, we aim to propose an end-to-end model to segment CTV for cervi...