AIMC Topic: Humans

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Physics guided neural networks for modelling of non-linear dynamics.

Neural networks : the official journal of the International Neural Network Society
The success of the current wave of artificial intelligence can be partly attributed to deep neural networks, which have proven to be very effective in learning complex patterns from large datasets with minimal human intervention. However, it is diffi...

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.

Basic & clinical pharmacology & toxicology
We sought to craft a drug safety signalling pipeline associating latent information in clinical free text with exposures to single drugs and drug pairs. Data arose from 12 secondary and tertiary public hospitals in two Danish regions, comprising appr...

Multivalued Logic for Optical Computing with Photonically Enabled Chiral Bio-organic Structures.

ACS nano
Photonic bio-organic multiphase structures are suggested here for integrated thin-film electronic nets with multilevel logic elements for multilevel computing via a reconfigurable photonic bandgap of chiral biomaterials. Herein, inspired by an artifi...

Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Digital pathology and artificial intelligence offer new opportunities for automatic histologic scoring. We applied a deep learning approach to IgA nephropathy biopsy images to develop an automatic histologic prognostic scor...

Artificial intelligence in healthcare: a primer for medical education in radiomics.

Personalized medicine
The application of artificial intelligence (AI) to healthcare has garnered significant enthusiasm in recent years. Despite the adoption of new analytic approaches, medical education on AI is lacking. We aim to create a usable AI primer for medical ed...

Deep neural networks constrained by neural mass models improve electrophysiological source imaging of spatiotemporal brain dynamics.

Proceedings of the National Academy of Sciences of the United States of America
Many efforts have been made to image the spatiotemporal electrical activity of the brain with the purpose of mapping its function and dysfunction as well as aiding the management of brain disorders. Here, we propose a non-conventional deep learning-b...

Effect of Robot-Assisted Training on Unilateral Spatial Neglect After Stroke: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Neurorehabilitation and neural repair
BACKGROUND: Several studies have shown that robotic devices can effectively improve motor function in stroke patients through limb activation. However, the effects of robot-assisted therapy on perceptual deficits after stroke is unclear.

Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations.

Sensors (Basel, Switzerland)
This paper presents a new synthetic dataset obtained from Gazebo simulations of an Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a Husky mobile robot equipped with a tridimensional (3D) Light Detection and Rangi...

Development of a Smart Chair Sensors System and Classification of Sitting Postures with Deep Learning Algorithms.

Sensors (Basel, Switzerland)
Nowadays in modern societies, a sedentary lifestyle is almost inevitable for a majority of the population. Long hours of sitting, especially in wrong postures, may result in health complications. A smart chair with the capability to identify sitting ...