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Exploring chemical space using natural language processing methodologies for drug discovery.
Drug discovery today
Feb 3, 2020
Text-based representations of chemicals and proteins can be thought of as unstructured languages codified by humans to describe domain-specific knowledge. Advances in natural language processing (NLP) methodologies in the processing of spoken languag...
Robust min-max optimal control design for systems with uncertain models: A neural dynamic programming approach.
Neural networks : the official journal of the International Neural Network Society
Jan 31, 2020
The design of an artificial neural network (ANN) based sub-optimal controller to solve the finite-horizon optimization problem for a class of systems with uncertainties is the main outcome of this study. The optimization problem considers a convex pe...
Dynamics of unidirectionally-coupled ring neural network with discrete and distributed delays.
Journal of mathematical biology
Jan 30, 2020
In this paper, we consider a ring neural network with one-way distributed-delay coupling between the neurons and a discrete delayed self-feedback. In the general case of the distribution kernels, we are able to find a subset of the amplitude death re...
Neural-network-based Motion Tracking for Breast Ultrasound Strain Elastography: An Initial Assessment of Performance and Feasibility.
Ultrasonic imaging
Jan 30, 2020
Accurate tracking of tissue motion is critically important for several ultrasound elastography methods. In this study, we investigate the feasibility of using three published convolution neural network (CNN) models built for optical flow (hereafter r...
Integration of the M6 Cyberknife in the Moderato Monte Carlo platform and prediction of beam parameters using machine learning.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jan 30, 2020
PURPOSE: This work describes the integration of the M6 Cyberknife in the Moderato Monte Carlo platform, and introduces a machine learning method to accelerate the modelling of a linac.
PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials.
Journal of chemical information and modeling
Jan 29, 2020
Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physicochemical properties of molecules and materials. Despite many successes, developing interpretable ANN architectures and im...
Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.
Scientific reports
Jan 29, 2020
Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clu...
Semantic and structural image segmentation for prosthetic vision.
PloS one
Jan 29, 2020
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...
Single-cell dispensing and 'real-time' cell classification using convolutional neural networks for higher efficiency in single-cell cloning.
Scientific reports
Jan 27, 2020
Single-cell dispensing for automated cell isolation of individual cells has gained increased attention in the biopharmaceutical industry, mainly for production of clonal cell lines. Here, machine learning for classification of cell images is applied ...
Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification Problem.
Molecules (Basel, Switzerland)
Jan 23, 2020
Drug-induced liver injury is a major concern in the drug development process. Expensive and time-consuming and studies do not reflect the complexity of the phenomenon. Complementary to wet lab methods are approaches, which present a cost-efficient...
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