AIMC Topic: Humans

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Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.

Biological psychiatry
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better un...

Multi-level feature interaction image super-resolution network based on convolutional nonlinear spiking neural model.

Neural networks : the official journal of the International Neural Network Society
Image super-resolution (ISR) is designed to recover lost detail information from low-resolution images, resulting in high-quality and high-definition high-resolution images. In the existing single ISR (SISR) methods based on convolutional neural netw...

Human-cobot collaboration's impact on success, time completion, errors, workload, gestures and acceptability during an assembly task.

Applied ergonomics
The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup. 120 participants realized a simple and a complex assembly task. 50% collaborated with another human (H/H) a...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Clinical pharmacology and therapeutics
Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to high-interindividual differences in effective dosage and the narrow therapeutic window. Model-informed precision dosing (MIPD) using machine learning...

Classification of exercise fatigue levels by multi-class SVM from ECG and HRV.

Medical & biological engineering & computing
Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classification of various exercise fatigue. In this study, we combine features extracted by deep neural networks with linear features from ECG and heart rat...

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

Talanta
In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Representative compounds of different families, including cocaine, 3,4-methylenedioxy-methamphetamine (MD...

Multi-scale relational graph convolutional network for multiple instance learning in histopathology images.

Medical image analysis
Graph convolutional neural networks have shown significant potential in natural and histopathology images. However, their use has only been studied in a single magnification or multi-magnification with either homogeneous graphs or only different node...

Neural critic learning with accelerated value iteration for nonlinear model predictive control.

Neural networks : the official journal of the International Neural Network Society
In practical industrial processes, the receding optimization solution of nonlinear model predictive control (NMPC) is always a very knotty problem. Based on adaptive dynamic programming, the accelerated value iteration predictive control (AVI-PC) alg...

Local spatial and temporal relation discovery model based on attention mechanism for traffic forecasting.

Neural networks : the official journal of the International Neural Network Society
Recognizing the evolution pattern of traffic condition and making accurate prediction play a vital role in intelligent transportation systems (ITS). With the massive increase of available traffic data, deep learning-based models have attracted consid...