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Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip.
BMC musculoskeletal disorders
Nov 13, 2024
OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radio...
Task-agnostic exoskeleton control via biological joint moment estimation.
Nature
Nov 13, 2024
Lower-limb exoskeletons have the potential to transform the way we move, but current state-of-the-art controllers cannot accommodate the rich set of possible human behaviours that range from cyclic and predictable to transitory and unstructured. We i...
Diagnostic performance of an artificial intelligence model for the detection of pneumothorax at chest X-ray.
Clinical imaging
Nov 12, 2024
PURPOSE: Pneumothorax (PTX) is a common clinical urgency, its diagnosis is usually performed on chest radiography (CXR), and it presents a setting where artificial intelligence (AI) methods could find terrain in aiding radiologists in facing increasi...
Recognizing and explaining driving stress using a Shapley additive explanation model by fusing EEG and behavior signals.
Accident; analysis and prevention
Nov 12, 2024
Driving stress is a critical factor leading to road traffic accidents. Despite numerous studies that have been conducted on driving stress recognition, most of them only focus on accuracy improvement without taking model interpretability into account...
[Incidence and determinants of viral load rebound in people receiving multi-month dispensing of antiretroviral therapy at the Regional Annex Hospital of Dschang from 2018-2023].
The Pan African medical journal
Nov 12, 2024
INTRODUCTION: in Cameroon, multi-month dispensing (MMD) of antiretrovirals (ARVs) was introduced to improve treatment adherence among people living with HIV (PLHIV). However, this strategy has limitations that may lead to viral load rebound. The purp...
Development and external validation of a machine learning model to predict diabetic nephropathy in T1DM patients in the real-world.
Acta diabetologica
Nov 11, 2024
AIMS: Studies on machine learning (ML) for the prediction of diabetic nephropathy (DN) in type 1 diabetes mellitus (T1DM) patients are rare. This study focused on the development and external validation of an explainable ML model to predict the risk ...
Impact of upper extremity robotic rehabilitation on respiratory parameters, functional capacity and dyspnea in patients with stroke: a randomized controlled study.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Nov 11, 2024
BACKGROUND: Stroke leads to reduced mobility and functional capacity, also negatively affects respiratory functions and muscle strength.
Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.
Applied psychology. Health and well-being
Nov 11, 2024
Social-emotional skills are vital for individual development, yet research on which skills most effectively promote students' mental and physical health, particularly from a global perspective, remains limited. This study aims to address this gap by ...
Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.
Journal of epidemiology and global health
Nov 11, 2024
BACKGROUND: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This st...
Deep-learning models reveal how context and listener attention shape electrophysiological correlates of speech-to-language transformation.
PLoS computational biology
Nov 11, 2024
To transform continuous speech into words, the human brain must resolve variability across utterances in intonation, speech rate, volume, accents and so on. A promising approach to explaining this process has been to model electroencephalogram (EEG) ...
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