AIMC Topic: Humans

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Combinatorial Bionic Hierarchical Flexible Strain Sensor for Sign Language Recognition with Machine Learning.

ACS applied materials & interfaces
Flexible strain sensors have been widely researched in fields such as smart wearables, human health monitoring, and biomedical applications. However, achieving a wide sensing range and high sensitivity of flexible strain sensors simultaneously remain...

[Relationship between certain uses of artificial intelligence and psychosocial risk factors in European work environments].

Archivos de prevencion de riesgos laborales
INTRODUCTION: To examine the relationship between the use of Artificial Intelligence (AI) to assess and monitor job performance and exposure to psychosocial risk factors, as well as associated adverse health effects in the European work environment.

FMCW Radar Human Action Recognition Based on Asymmetric Convolutional Residual Blocks.

Sensors (Basel, Switzerland)
Human action recognition based on optical and infrared video data is greatly affected by the environment, and feature extraction in traditional machine learning classification methods is complex; therefore, this paper proposes a method for human acti...

Novel AT2 Cell Subpopulations and Diagnostic Biomarkers in IPF: Integrating Machine Learning with Single-Cell Analysis.

International journal of molecular sciences
Idiopathic pulmonary fibrosis (IPF) is a long-term condition with an unidentified cause, and currently there are no specific treatment options available. Alveolar epithelial type II cells (AT2) constitute a heterogeneous population crucial for secret...

Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning.

BMC public health
BACKGROUND: Increased costs in the health sector have put considerable strain on the public budgets allocated to pharmaceutical purchases. Faced with such pressures amplified by financial crises and pandemics, national purchasing authorities are pres...

Treatment with robot-assisted gait trainer Walkbot along with physiotherapy vs. isolated physiotherapy in children and adolescents with cerebral palsy. Experimental study.

BMC neurology
BACKGROUND: Improving walking ability is a key objective in the treatment of children and adolescents with cerebral palsy, since it directly affects their activity and participation. In recent years, robotic technology has been implemented in gait tr...

Advancing medical imaging: detecting polypharmacy and adverse drug effects with Graph Convolutional Networks (GCN).

BMC medical imaging
Polypharmacy involves an individual using many medications at the same time and is a frequent healthcare technique used to treat complex medical disorders. Nevertheless, it also presents substantial risks of negative medication responses and interact...

Detecting depression severity using weighted random forest and oxidative stress biomarkers.

Scientific reports
This study employs machine learning to detect the severity of major depressive disorder (MDD) through binary and multiclass classifications. We compared models that used only biomarkers of oxidative stress with those that incorporate sociodemographic...

Promoting safety of underground machinery operators through participatory ergonomics and fuzzy model analysis to foster sustainable mining practices.

Scientific reports
One of the most vital parameters to achieve sustainability in any field is encompassing the Occupational Health and Safety (OHS) of the workers. In mining industry where heavy earth moving machineries are largely employed, ergonomic hazards turn out ...