AIMC Topic: Deep Learning

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COVID-19 Diagnosis Using an Enhanced Inception-ResNetV2 Deep Learning Model in CXR Images.

Journal of healthcare engineering
The COVID-19 pandemic has a significant negative effect on people's health, as well as on the world's economy. Polymerase chain reaction (PCR) is one of the main tests used to detect COVID-19 infection. However, it is expensive, time-consuming, and l...

A deep transfer learning framework for the automated assessment of corneal inflammation on in vivo confocal microscopy images.

PloS one
PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in compute...

Multi-View Mammographic Density Classification by Dilated and Attention-Guided Residual Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Breast density is widely adopted to reflect the likelihood of early breast cancer development. Existing methods of mammographic density classification either require steps of manual operations or achieve only moderate classification accuracy due to t...

MRI Based Radiomics Approach With Deep Learning for Prediction of Vessel Invasion in Early-Stage Cervical Cancer.

IEEE/ACM transactions on computational biology and bioinformatics
This article aims to build deep learning-based radiomic methods in differentiating vessel invasion from non-vessel invasion in cervical cancer with multi-parametric MRI data. A set of 1,070 dynamic T1 contrast-enhanced (DCE-T1) and 986 T2 weighted im...

Knowledge-Powered Deep Breast Tumor Classification With Multiple Medical Reports.

IEEE/ACM transactions on computational biology and bioinformatics
Breast tumor classification with multiple medical reports such as B-ultrasound, Mammography (X-ray) and Nuclear Magnetic Resonance Imaging (MRI) is crucial to the intelligent cancer diagnosis system. Unlike the other domain texts, the medical reports...

A Method of Information Protection for Collaborative Deep Learning under GAN Model Attack.

IEEE/ACM transactions on computational biology and bioinformatics
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...

High-Risk Prediction of Cardiovascular Diseases via Attention-Based Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
High-risk prediction of cardiovascular disease is of great significance and impendency in medical fields with the increasing phenomenon of sub-health these years. Most existing pathological methods for the prognosis prediction are either costly or pr...

A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Retinal vessel segmentation is a critical procedure towards the accurate visualization, diagnosis, early treatment, and surgery planning of ocular diseases. Recent deep learning-based approaches have achieved impressive performance in retinal vessel ...

Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN.

IEEE/ACM transactions on computational biology and bioinformatics
Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this disease. Computer-aided diagnosis of pneumothorax on chest X-ray, as a prerequisite for a timely cur...

U-Net Deep-Learning-Based 3D Cell Counter for the Quality Control of 3D Cell-Based Assays through Seed Cell Measurement.

SLAS technology
Conventional cell-counting software uses contour or watershed segmentations and focuses on identifying two-dimensional (2D) cells attached on the bottom of plastic plates. Recently developed software has been useful tools for the quality control of 2...