Latest AI and machine learning research in practice management for healthcare professionals.
Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify di...
BACKGROUND: Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which...
INTRODUCTION: MicroRNAs (miRNAs or miRs) are non-coding RNAs. Studies have shown that miRNAs are exp...
The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consist...
Area V4 is the first object-specific processing stage in the ventral visual pathway, just as area MT...
Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology ...
Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide signi...
Long non-coding RNA (LncRNA) and microRNA (miRNA) are both non-coding RNAs that play significant reg...
Machine learning (ML) offers robust statistical and probabilistic techniques that can help to make s...
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...