AIMC Topic: Young Adult

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Deep learning-based acceleration of muscle water T2 mapping in patients with neuromuscular diseases by more than 50% - translating quantitative MRI from research to clinical routine.

PloS one
BACKGROUND: Quantitative muscle water T2 (T2w) mapping is regarded as a biomarker for disease activity and response to treatment in neuromuscular diseases (NMD). However, the implementation in clinical settings is limited due to long scanning times a...

Neuro-Modulation Analysis Based on Muscle Synergy Graph Neural Network in Human Locomotion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The coordination of muscles in human locomotion is commonly understood as the integration of motor modules known as muscle synergies. Recent research has delved into the adaptation of muscle synergies during the acquisition of new motor skills. Howev...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Comprehensive psychiatry
Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natural language processing and machine learning to analyse a large dataset of self-reported rates of and...

Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose.

BMC research notes
OBJECTIVE: Sex determination is an important parameter for personal identification in forensic and medico-legal examinations. The study aims at predicting sex accuracy from different parameters of ear and nose by using a novel approach of Machine Lea...

A prediction model of pediatric bone density from plain spine radiographs using deep learning.

Scientific reports
Osteoporosis, a bone disease characterized by decreased bone mineral density (BMD) resulting in decreased mechanical strength and an increased fracture risk, remains poorly understood in children. Herein, we developed/validated a deep learning-based ...

Brain-guided convolutional neural networks reveal task-specific representations in scene processing.

Scientific reports
Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its ...

The spatiotemporal ecology of Oropouche virus across Latin America: a multidisciplinary, laboratory-based, modelling study.

The Lancet. Infectious diseases
BACKGROUND: Latin America has been experiencing an Oropouche virus (OROV) outbreak of unprecedented magnitude and spread since 2023-24 for unknown reasons. We aimed to identify risk predictors of and areas at risk for OROV transmission.

Predicting Maximal Military Occupational Task Performance from Physical Fitness Tests Using Machine Learning.

Medicine and science in sports and exercise
PURPOSE: Optimal performance in military tasks is crucial for operational success. These tasks are often simulated in training, assessing personnel performance within a military environment. However, these assessments are time-consuming and a potenti...

Our tools redefine what it means to be us: perceived robotic agency decreases the importance of agency in humanity.

BMC psychology
Past work has primarily focused on how the perception of robotic agency influences human-robot interaction and the evaluation of robotic progress, while overlooking its impact on reconsidering what it means to be human. Drawing on social identity the...