AIMC Topic: Humans

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User-Intended Doppler Measurement Type Prediction Combining CNNs With Smart Post-Processing.

IEEE journal of biomedical and health informatics
Spectral Doppler measurements are an important part of the standard echocardiographic examination. These measurements give insight into myocardial motion and blood flow, providing clinicians with parameters for diagnostic decision making. Many of the...

DBAN: Adversarial Network With Multi-Scale Features for Cardiac MRI Segmentation.

IEEE journal of biomedical and health informatics
With the development of medical artificial intelligence, automatic magnetic resonance image (MRI) segmentation method is quite desirable. Inspired by the power of deep neural networks, a novel deep adversarial network, dilated block adversarial netwo...

Improving Deep Reinforcement Learning With Transitional Variational Autoencoders: A Healthcare Application.

IEEE journal of biomedical and health informatics
Reinforcement learning is a powerful tool for developing personalized treatment regimens from healthcare data. Yet training reinforcement learning agents through direct interactions with patients is often impractical for ethical reasons. One solution...

Multi-Parametric Fusion of 3D Power Doppler Ultrasound for Fetal Kidney Segmentation Using Fully Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Kidney development is key to the long-term health of the fetus. Renal volume and vascularity assessed by 3D ultrasound (3D-US) are known markers of wellbeing, however, a lack of real-time image segmentation solutions preclude these measures being use...

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...

Predicting the Prognosis of MCI Patients Using Longitudinal MRI Data.

IEEE/ACM transactions on computational biology and bioinformatics
The aim of this study is to develop a computer-aided diagnosis system with a deep-learning approach for distinguishing "Mild Cognitive Impairment (MCI) due to Alzheimer's Disease (AD)" patients among a list of MCI patients. In this system we are usin...

CNN-RNN Based Intelligent Recommendation for Online Medical Pre-Diagnosis Support.

IEEE/ACM transactions on computational biology and bioinformatics
The rapidly developed Health 2.0 technology has provided people with more opportunities to conduct online medical consultation than ever before. Understanding contexts within different online medical communications and activities becomes a significan...

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...