AIMC Topic: Neural Networks, Computer

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Deep Feature Representations for Variable-Sized Regions of Interest in Breast Histopathology.

IEEE journal of biomedical and health informatics
OBJECTIVE: Modeling variable-sized regions of interest (ROIs) in whole slide images using deep convolutional networks is a challenging task, as these networks typically require fixed-sized inputs that should contain sufficient structural and contextu...

Design Comorbidity Portfolios to Improve Treatment Cost Prediction of Asthma Using Machine Learning.

IEEE journal of biomedical and health informatics
Comorbidity is an important factor to consider when trying to predict the cost of treating asthma patients. When an asthmatic patient suffered from comorbidity, the cost of treating such a patient becomes dependent on the nature of the comorbidity. T...

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...

Multimodal Sensor Motion Intention Recognition Based on Three-Dimensional Convolutional Neural Network Algorithm.

Computational intelligence and neuroscience
With the development of microelectronic technology and computer systems, the research of motion intention recognition based on multimodal sensors has attracted the attention of the academic community. Deep learning and other nonlinear neural network ...

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...

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...