IEEE transactions on neural networks and learning systems
Oct 26, 2015
Associative memories are data structures that allow retrieval of previously stored messages given part of their content. They, thus, behave similarly to the human brain's memory that is capable, for instance, of retrieving the end of a song, given it...
Neural networks : the official journal of the International Neural Network Society
Sep 5, 2015
In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel...
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Aug 5, 2015
The acceleration of solid dosage form product development can be facilitated by the inclusion of excipients that exhibit poly-/multi-functionality with reduction of the time invested in multiple excipient optimisations. Because active pharmaceutical ...
Machine learning techniques are of great importance in the analysis of microarray expression data, and provide a systematic and promising way to predict core cancer genes. In this study, a hybrid strategy was introduced based on machine learning tech...
It is well-known that a spontaneous reporting system suffers from significant under-reporting of adverse drug reactions from the source population. The existing methods do not adjust for such under-reporting for the calculation of measures of associa...
Proceedings of the National Academy of Sciences of the United States of America
Jun 15, 2021
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2019
OBJECTIVE: The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method.