AIMC Topic: Neural Networks, Computer

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Machine learning in medicine: a practical introduction.

BMC medical research methodology
BACKGROUND: Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providi...

LSTM Model for Prediction of Heart Failure in Big Data.

Journal of medical systems
The combination of big data and deep learning is a world-shattering technology that can make a great impact on any industry if used in a proper way. With the availability of large volume of health care datasets and progressions in deep learning techn...

Blood Cell Classification Based on Hyperspectral Imaging With Modulated Gabor and CNN.

IEEE journal of biomedical and health informatics
Cell classification, especially that of white blood cells, plays a very important role in the field of diagnosis and control of major diseases. Compared to traditional optical microscopic imaging, hyperspectral imagery, combined with both spatial and...

Scalable Digital Neuromorphic Architecture for Large-Scale Biophysically Meaningful Neural Network With Multi-Compartment Neurons.

IEEE transactions on neural networks and learning systems
Multicompartment emulation is an essential step to enhance the biological realism of neuromorphic systems and to further understand the computational power of neurons. In this paper, we present a hardware efficient, scalable, and real-time computing ...

Augmenting Recurrent Neural Networks Resilience by Dropout.

IEEE transactions on neural networks and learning systems
This brief discusses the simple idea that dropout regularization can be used to efficiently induce resiliency to missing inputs at prediction time in a generic neural network. We show how the approach can be effective on tasks where imputation strate...

Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics
As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficult to cure. However, the advent of precision medicine provides an opportunity to improve the treatment of lung cancer. Subtyping lung cancer plays an ...

Data-driven synthetic MRI FLAIR artifact correction via deep neural network.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: FLAIR (fluid attenuated inversion recovery) imaging via synthetic MRI methods leads to artifacts in the brain, which can cause diagnostic limitations. The main sources of the artifacts are attributed to the partial volume effect and flow,...

Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks.

European journal of sport science
First and second ventilatory thresholds (VT and VT) represent the boundaries of the moderate-heavy and heavy-severe exercise intensity. Currently, VTs are primarily detected visually from cardiopulmonary exercise test (CPET) data, beginning with an i...

Multi-scale gradual integration CNN for false positive reduction in pulmonary nodule detection.

Neural networks : the official journal of the International Neural Network Society
Lung cancer is a global and dangerous disease, and its early detection is crucial for reducing the risks of mortality. In this regard, it has been of great interest in developing a computer-aided system for pulmonary nodules detection as early as pos...