International journal of nanomedicine
Jul 23, 2019
Artificial intelligence (AI) integrated circuits (IC) have memory devices as the key component. Due to more complex algorithms and architectures required by neuroscience and other medical applications, various memory structures have been widely prop...
Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend ...
Disability and rehabilitation. Assistive technology
Jul 22, 2019
BACKGROUND: More than 70% of elderly people age 80 and older are experiencing problems in personal mobility. Assistive robotics can represent a concrete support providing also a support for caregivers, clinicians and nurses by reducing their burden.
Proceedings of the National Academy of Sciences of the United States of America
Jul 22, 2019
Neurodevelopmental spectrum disorders like autism (ASD) are diagnosed, on average, beyond age 4 y, after multiple critical periods of brain development close and behavioral intervention becomes less effective. This raises the urgent need for quantita...
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)-a type of simple artificial neural network...
BACKGROUND: Few investigations to date assessing the effectiveness of robot-assisted intersphincteric resection (ISR) have included sufficient patients and follow-up period. This study assessed the utility and safety of robot-assisted ISR by comparin...
BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-stage hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE).
International journal of radiation oncology, biology, physics
Jul 22, 2019
PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of great help in glioma management. This study aimed to create a highly accurate machine learning model to perform glioma grading.
Machine learning analyses allow for the consideration of numerous variables in order to accommodate complex relationships that would not otherwise be apparent in traditional statistical methods to better classify patient risk. The SPLIT registry data...
BACKGROUND: Functional integration or connectivity in brain is directional, non-linear as well as variable in time-lagged dependence. Deep neural networks (DNN) have become an indispensable tool everywhere, by learning higher levels of abstract and c...
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