AIMC Topic: Humans

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CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.

Scientific data
Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...

Implementing ensemble of deep learning model with optimization techniques for human activity recognition to assist individuals with disabilities.

Scientific reports
Recent human activity recognition (HAR) developments have allowed numerous applications like healthcare, smart homes, and improved manufacturing. Activity recognition plays a crucial part in improving human well-being by capturing behavioral data, en...

Enhancing disease clustering through symptom-based analysis and large language model interpretations.

Scientific reports
Humans face various diseases that are mainly caused by environmental conditions and living habits. These diseases exhibit several symptoms and can share a relationship based on their symptoms. The identification and interpretation of these groups of ...

Exploring the impact mechanisms of EEG signals and emotional intelligence levels on language learning efficiency.

Scientific reports
Improving language learning through a better understanding of how brain activity and emotional intelligence interact is a promising research direction with practical value in education. Traditional methods in this area often use static models, which ...

DANet a lightweight dilated attention network for malaria parasite detection.

Scientific reports
Malaria remains a critical global health challenge, requiring accurate and efficient diagnostic tools, particularly in developing countries with limited medical expertise. Detecting malaria parasites from red blood cell (RBC) blood smear images is ch...

A lightweight network for brain MRI segmentation.

Scientific reports
Brain MRI segmentation plays a crucial role in medical imaging, aiding in the identification and monitoring of brain diseases. This research presents a novel deep learning-based framework designed to achieve high segmentation accuracy while maintaini...

Individual differences in anthropomorphism help explain social connection to AI companions.

Scientific reports
People increasingly use conversational AI for support and companionship. Yet, current discourse on AI companions reveals a stark divide: some scholars argue that feeling connected to AI is impossible due to AI's inability to experience emotions, whil...

A novel framework for COPD management in cyber-physical systems using machine learning.

Scientific reports
Chronic Obstructive Pulmonary Disease (COPD) exacerbations pose significant challenges to healthcare systems due to their unpredictable nature and severe impact on patients. Current COPD prediction models often lack real-time capabilities and fail to...

Efficient elastic tissue motions indicate general motor skill.

Scientific reports
Insights into the general nature of motor skill could fundamentally change how we develop movement abilities, with implications for musculoskeletal well-being and injury. Here, we sought to identify indicators of general motor skill-those shared by e...

Using Artificial Intelligence-Based Technologies for the Early Detection of Behavioral and Psychological Symptoms of Dementia: Scoping Review.

JMIR aging
BACKGROUND: People with dementia commonly display behavioral and psychological symptoms, which have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to support earlier detection of the behavioral an...