AIMC Topic: Neural Networks, Computer

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MutBLESS: A tool to identify disease-prone sites in cancer using deep learning.

Biochimica et biophysica acta. Molecular basis of disease
Understanding the molecular basis and impact of mutations at different stages of cancer are long-standing challenges in cancer biology. Identification of driver mutations from experiments is expensive and time intensive. In the present study, we coll...

Structure and function in artificial, zebrafish and human neural networks.

Physics of life reviews
Network science provides a set of tools for the characterization of the structure and functional behavior of complex systems. Yet a major problem is to quantify how the structural domain is related to the dynamical one. In other words, how the divers...

Tree-structured neural networks: Spatiotemporal dynamics and optimal control.

Neural networks : the official journal of the International Neural Network Society
How the network topology drives the response dynamic is a basic question that has not yet been fully answered in neural networks. Elucidating the internal relation between topological structures and dynamics is instrumental in our understanding of br...

Stability analysis of stochastic gradient descent for homogeneous neural networks and linear classifiers.

Neural networks : the official journal of the International Neural Network Society
We prove new generalization bounds for stochastic gradient descent when training classifiers with invariances. Our analysis is based on the stability framework and covers both the convex case of linear classifiers and the non-convex case of homogeneo...

A novel time series prediction method based on pooling compressed sensing echo state network and its application in stock market.

Neural networks : the official journal of the International Neural Network Society
In the prediction of time series, the echo state network (ESN) exhibits exclusive strengths and a unique training structure. Based on ESN model, a pooling activation algorithm consisting noise value and adjusted pooling algorithm is proposed to enric...

Long short-term memory with activation on gradient.

Neural networks : the official journal of the International Neural Network Society
As the number of long short-term memory (LSTM) layers increases, vanishing/exploding gradient problems exacerbate and have a negative impact on the performance of the LSTM. In addition, the ill-conditioned problem occurs in the training process of LS...

An enhanced Runge Kutta boosted machine learning framework for medical diagnosis.

Computers in biology and medicine
With the development and maturity of machine learning methods, medical diagnosis aided with machine learning methods has become a popular method to assist doctors in diagnosing and treating patients. However, machine learning methods are greatly affe...

Detecting Pre-Analytically Delayed Blood Samples for Laboratory Diagnostics Using Raman Spectroscopy.

International journal of molecular sciences
In this proof-of-principle study, we systematically studied the potential of Raman spectroscopy for detecting pre-analytical delays in blood serum samples. Spectra from 330 samples from a liver cirrhosis cohort were acquired over the course of eight ...

Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout.

Physics in medicine and biology
. Radiation therapy for head and neck (H&N) cancer relies on accurate segmentation of the primary tumor. A robust, accurate, and automated gross tumor volume segmentation method is warranted for H&N cancer therapeutic management. The purpose of this ...

The potential for clinical application of automatic quantification of olfactory bulb volume in MRI scans using convolutional neural networks.

NeuroImage. Clinical
The olfactory bulbs (OBs) play a key role in olfactory processing; their volume is important for diagnosis, prognosis and treatment of patients with olfactory loss. Until now, measurements of OB volumes have been limited to quantification of manually...