AIMC Topic: Humans

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Robot-assisted gait training for individuals with severe acquired brain injury: a scoping review.

Brain injury
INTRODUCTION: Early out-of-bed mobilization is recommended for individuals with severe acquired brain injury and impaired consciousness to promote recovery. Robot-assisted gait training (RAGT) utilizes robotic assistance to facilitate neuroplastic ch...

Cyclist crash severity modeling: A hybrid approach of XGBoost-SHAP and random parameters logit with heterogeneity in means and variances.

Journal of safety research
INTRODUCTION: Across the globe, policymakers are focusing on boosting sustainable transport options, notably cycling, to foster eco-friendly urban environments. However, the persistent safety challenges cyclists face continues to hinder these efforts...

Development and Validation of a Novel Prediction Model for Hearing Loss From Cisplatin Chemotherapy.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Cisplatin treats many common tumors but causes permanent and debilitating hearing loss (HL). The objective of this study was to develop and externally validate a predictive model of HL in cisplatin-treated children and adolescent cancer surv...

Entropy-driven deep learning framework for epilepsy detection using electro encephalogram signals.

Neuroscience
Epilepsy is one of the most frequently occurring neurological disorders that require early and accurate detection. This paper introduces a novel approach for the automatic identification of epilepsy in EEG signals by incorporating advanced entropy-ba...

Optimizing elderly care: A data-driven AI model for predicting polypharmacy risk in the elderly using SHARE data.

Neuroscience
BACKGROUND: Aging is frequently accompanied by multimorbidity, the presence of multiple chronic conditions, which contributes to declines in both cognitive and physical function and presents complex health challenges. One such challenge is Polypharma...

Effective Autism Classification Through Grasping Kinematics.

Autism research : official journal of the International Society for Autism Research
Autism is a complex neurodevelopmental condition, where motor abnormalities play a central role alongside social and communication difficulties. These motor symptoms often manifest in early childhood, making them critical targets for early diagnosis ...

A Novel 3D Approach with a CNN and Swin Transformer for Decoding EEG-Based Motor Imagery Classification.

Sensors (Basel, Switzerland)
Motor imagery (MI) is a crucial research field within the brain-computer interface (BCI) domain. It enables patients with muscle or neural damage to control external devices and achieve movement functions by simply imagining bodily motions. Despite t...

MDEU-Net: Medical Image Segmentation Network Based on Multi-Head Multi-Scale Cross-Axis.

Sensors (Basel, Switzerland)
Significant advances have been made in the application of attention mechanisms to medical image segmentation, and these advances are notably driven by the development of the cross-axis attention mechanism. However, challenges remain in handling compl...

Development and evaluation of the COntextualised and Personalised Physical activity and Exercise Recommendations (COPPER) Ontology.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Personalised recommendations for action and coping plans for physical activity (PA) may reduce user burden and increase plan quality. Ontologies are a promising alternative to existing black-box approaches for creating such personalised r...

Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.

BMC medical imaging
Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR) depend on accurately segmenting retinal vessels, which can be achieved through the invasive techni...