AIMC Topic: Deep Learning

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A deep learning approach identifies new ECG features in congenital long QT syndrome.

BMC medicine
BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying mutations. Most general cardiologists do not routinely see patients with congenital LQTS and may not always recognize the accompanying ECG features. I...

Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy.

The Analyst
Nucleated red blood cells (NRBCs) as a type of rare cell present in an adult's peripheral blood is a concern in hematology, intensive care medicine and prenatal diagnostics. However, it is labor-intensive to screen such rare cells from real complex c...

Identifying the charge density and dielectric environment of graphene using Raman spectroscopy and deep learning.

The Analyst
The impact of the environment on the properties of graphene such as strain, charge density, and dielectric environment can be evaluated by Raman spectroscopy. These environmental interactions are not trivial to determine since they affect the spectra...

A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

Cancer medicine
BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of...

Diagnosis of COVID-19 patients by adapting hyper parametertuned deep belief network using hosted cuckoo optimization algorithm.

Electromagnetic biology and medicine
COVID-19 is an infection caused by recently discovered corona virus. The symptoms of COVID-19 are fever, cough and dumpiness of breathing. A quick and accurate identification is essential for an efficient fight against COVID-19. A machine learning te...

Brain network connectivity feature extraction using deep learning for Alzheimer's disease classification.

Neuroscience letters
Early diagnosis and therapeutic intervention for Alzheimer's disease (AD) is currently the only viable option for improving clinical outcomes. Combining structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imag...

A deep learning-based segmentation system for rapid onsite cytologic pathology evaluation of pancreatic masses: A retrospective, multicenter, diagnostic study.

EBioMedicine
BACKGROUND: We aimed to develop a deep learning-based segmentation system for rapid on-site cytopathology evaluation (ROSE) to improve the diagnostic efficiency of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) biopsy.

Reconstruction of Dexterous 3D Motion Data From a Flexible Magnetic Sensor With Deep Learning and Structure-Aware Filtering.

IEEE transactions on visualization and computer graphics
We propose IM3D+, a novel approach to reconstructing 3D motion data from a flexible magnetic flux sensor array using deep learning and a structure-aware temporal bilateral filter. Computing the 3D configuration of markers (inductor-capacitor (LC) coi...

Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification.

IEEE transactions on medical imaging
Deep convolutional neural network (DCNN) models have been widely explored for skin disease diagnosis and some of them have achieved the diagnostic outcomes comparable or even superior to those of dermatologists. However, broad implementation of DCNN ...

Deep Learning Based Joint PET Image Reconstruction and Motion Estimation.

IEEE transactions on medical imaging
Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion can be estimated simultaneously from respiratory gated data through a joint estimation framework. H...