AIMC Topic: Humans

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Multifunctional Electronic Skins Enable Robots to Safely and Dexterously Interact with Human.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Human-robot collaboration is playing more and more important roles in current deployments of robotic systems in our lives. Haptic perception and intelligent control are essential to ensure safety and efficiency of human-robot interaction. However, ex...

Flexible Neural Network Realized by the Probabilistic SiO Memristive Synaptic Array for Energy-Efficient Image Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The human brain's neural networks are sparsely connected via tunable and probabilistic synapses, which may be essential for performing energy-efficient cognitive and intellectual functions. In this sense, the implementation of a flexible neural netwo...

Structure-aware siamese graph neural networks for encounter-level patient similarity learning.

Journal of biomedical informatics
Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given patient and patient records in the database could contribute to clinical references for diagnosis and me...

Predicting machine's performance record using the stacked long short-term memory (LSTM) neural networks.

Journal of applied clinical medical physics
PURPOSE: The record of daily quality control (QC) items shows machine performance patterns and potentially provides warning messages for preventive actions. This study developed a neural network model that could predict the record and trend of data v...

Improving Radar Human Activity Classification Using Synthetic Data with Image Transformation.

Sensors (Basel, Switzerland)
Machine Learning (ML) methods have become state of the art in radar signal processing, particularly for classification tasks (e.g., of different human activities). Radar classification can be tedious to implement, though, due to the limited size and ...

Brains and algorithms partially converge in natural language processing.

Communications biology
Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown. Here, we systemat...

Thermography based skin allergic reaction recognition by convolutional neural networks.

Scientific reports
In this work we present an automated approach to allergy recognition based on neural networks. Allergic reaction classification is an important task in modern medicine. Currently it is done by humans, which has obvious drawbacks, such as subjectivity...

A machine learning model for predicting deterioration of COVID-19 inpatients.

Scientific reports
The COVID-19 pandemic has been spreading worldwide since December 2019, presenting an urgent threat to global health. Due to the limited understanding of disease progression and of the risk factors for the disease, it is a clinical challenge to predi...

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers.

Scientific reports
Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular degeneration (AMD), a degenerative retinal disease which leads to blindness if untreated. Optical coherence tomography angiography (OCTA) has become a p...