AIMC Topic: Neural Networks, Computer

Clear Filters Showing 30661 to 30670 of 31376 articles

Chaos versus noise as drivers of multistability in neural networks.

Chaos (Woodbury, N.Y.)
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...

Application of the advanced oxidative process on the degradation of the green leaf and purple açaí food dyes with kinetic monitoring and artificial neural network modelling.

Water science and technology : a journal of the International Association on Water Pollution Research
The study evaluated the advanced oxidative processes concerning the degradation of green leaf and purple açaí dyes, as well as the prediction of data through artificial neural networks (ANNs). It was verified that percentage of degradation on the wav...

Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We executed the Social Media Mining for Health (SMM4H) 2017 shared tasks to enable the community-driven development and large-scale evaluation of automatic text processing methods for the classification and normalization of health-related ...

A Dynamical Systems Perspective on Flexible Motor Timing.

Trends in cognitive sciences
A hallmark of higher brain function is the ability to rapidly and flexibly adjust behavioral responses based on internal and external cues. Here, we examine the computational principles that allow decisions and actions to unfold flexibly in time. We ...

If It Only Had a Brain: What "Neuro" Means for Science and Ethics.

Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees

Can Machine-learning Techniques Be Used for 5-year Survival Prediction of Patients With Chondrosarcoma?

Clinical orthopaedics and related research
BACKGROUND: Several studies have identified prognostic factors for patients with chondrosarcoma, but there are few studies investigating the accuracy of computationally intensive methods such as machine learning. Machine learning is a type of artific...

Artificial intelligence in the diagnosis of Parkinson's disease from ioflupane-123 single-photon emission computed tomography dopamine transporter scans using transfer learning.

Nuclear medicine communications
OBJECTIVE: The objective of this study was to identify the extent to which artificial intelligence could be used in the diagnosis of Parkinson's disease from ioflupane-123 (¹²³I) single-photon emission computed tomography (SPECT) dopamine transporter...

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoin...

SegAN: Adversarial Network with Multi-scale L Loss for Medical Image Segmentation.

Neuroinformatics
Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single ...

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

Bioinformatics (Oxford, England)
MOTIVATION: In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-res...