AIMC Topic: Young Adult

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Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

BMJ open
INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often necessitating surgical intervention. Deep brain stimulation (DBS) of the thalamus has been introduc...

AI-powered remote monitoring of brain responses to clear and incomprehensible speech via speckle pattern analysis.

Journal of biomedical optics
SIGNIFICANCE: Functional magnetic resonance imaging provides high spatial resolution but is limited by cost, infrastructure, and the constraints of an enclosed scanner. Portable methods such as functional near-infrared spectroscopy and electroencepha...

Contribution of Labrum and Cartilage to Joint Surface in Different Hip Deformities: An Automatic Deep Learning-Based 3-Dimensional Magnetic Resonance Imaging Analysis.

The American journal of sports medicine
BACKGROUND: Multiple 2-dimensional magnetic resonance imaging (MRI) studies have indicated that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for ...

How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.

BMC psychology
INTRODUCTION: Artificial Intelligence (AI) has become part of our everyday lives and is also increasingly applied in psychosocial healthcare as it can enhance it, make it more accessible, and reduce barriers for help seeking. User behaviour and readi...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Scientific reports
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome.

Scientific reports
Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients' quality of life, primarily due to impaired motor function and gait instability. Although conventional neurol...

Emotion recognition with multiple physiological parameters based on ensemble learning.

Scientific reports
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...

"Calming the nightmares": A qualitative study of a socially assistive robot for sensory and emotional support in individuals with eating disorders and PTSD.

PloS one
Individuals with eating disorders (ED) and co-occurring post-traumatic stress disorder (PTSD) often face difficulties with sensory overload and emotion regulation (ER), which can make treatment more complex. Assistive devices that offer real-time sup...

First impressions of a humanoid social robot with natural language capabilities.

Scientific reports
Concurrent developments in robotic design and natural language processing (NLP) have enabled the production of humanoid chatbots that can operate in commercial and community settings. Though still novel, the presence of physically embodied social rob...