AIMC Topic: Humans

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A machine learning framework for predicting drug-drug interactions.

Scientific reports
Understanding drug-drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a hig...

5G-enabled contactless multi-user presence and activity detection for independent assisted living.

Scientific reports
Wireless sensing is the state-of-the-art technique for next generation health activity monitoring. Smart homes and healthcare centres have a demand for multi-subject health activity monitoring to cater for future requirements. 5G-sensing coupled with...

Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: For rehabilitation training systems, it is essential to automatically record and recognize exercises, especially when more than one type of exercise is performed without a predefined sequence. Most motion recognition methods are based on ...

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.

eLife
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few ...

Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

PloS one
Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in h...

Predicting affinity ties in a surname network.

PloS one
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data. This network is a multi-relational graph with nodes representing surnames and edges representing the prevalence of i...

Deep Q-network-based traffic signal control models.

PloS one
Traffic congestion has become common in urban areas worldwide. To solve this problem, the method of searching a solution using artificial intelligence has recently attracted widespread attention because it can solve complex problems such as traffic s...

Classifying muscle parameters with artificial neural networks and simulated lateral pinch data.

PloS one
OBJECTIVE: Hill-type muscle models are widely employed in simulations of human movement. Yet, the parameters underlying these models are difficult or impossible to measure in vivo. Prior studies demonstrate that Hill-type muscle parameters are encode...