Latest AI and machine learning research in practice management for healthcare professionals.
A non-coding RNA (ncRNA) is a kind of RNA that is not converted into protein, however, it is involve...
OBJECTIVE: We have developed and validated a novel EEG-based signal processing approach to distingui...
Predictive coding (PC) networks are a biologically interesting class of neural networks. Their layer...
Multiscale geometric analysis (MGA) is not only characterized by multi-resolution, time-frequency lo...
Although many authors have highlighted the importance of predicting people's health costs to improve...
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex ...
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achiev...
Cortical networks are complex systems of a great many interconnected neurons that operate from colle...
The application of machine learning (ML) for use in generating insights and making predictions on ne...
Understanding patient responses to psychotherapy is important in developing effective interventions...
Accurate, automated extraction of clinical stroke information from unstructured text has several imp...
We propose a new supervised learning rule for multilayer spiking neural networks (SNNs) that use a f...
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypogly...
Many proteins exist in natures as oligomers with various quaternary structural attributes rather tha...
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administ...
OBJECTIVE: This study aims to develop and evaluate effective methods that can normalize diagnosis an...
Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. ...
This article considers implementation of artificial neural networks (ANNs) using molecular computing...
Reconstructing a "forma mentis", a mindset, and its changes, means capturing how individuals perceiv...
Following a stimulus, the neural response typically strongly varies in time and across neurons befor...
In this paper, we present an effective deep prediction framework based on robust recurrent neural ne...