Monitoring and Detecting Wandering Behavior in Persons with Dementia Using a Bluetooth Low Energy Localization System
A Bluetooth Low Energy-based localization system can effectively monitor and detect wandering behavior in persons with dementia, providing crucial information to caregivers.
ADMarker: A Multi-Modal Federated Learning System for Detecting Digital Biomarkers of Alzheimer's Disease
ADMarker is the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms to accurately detect a comprehensive set of multidimensional digital biomarkers of Alzheimer's disease in a privacy-preserving manner.
Revolutionizing Bacterial Identification with Inkjet Bioprinter
Innovative inkjet bioprinter revolutionizes bacterial identification, leading to faster and more accurate treatment decisions.
KG-Rank: Enhancing Medical QA with Knowledge Graphs and Ranking Techniques
KG-Rank integrates knowledge graphs and ranking techniques to enhance medical question-answering accuracy.
LightSword: A Customized Virtual Reality Exergame for Long-Term Cognitive Inhibition Training in Older Adults
Customized VR exergame LightSword enhances cognitive inhibition in older adults for long-term training.
Artificial Intelligence Enables Paralyzed Woman to Speak Through Avatar
AI enables paralyzed woman to communicate through digital avatar, revolutionizing speech synthesis.
TSRNet: Real-Time ECG Anomaly Detection Framework
ECG anomaly detection using multimodal time and spectrogram restoration network.
The Revolutionary Impact of Smart Pills on Healthcare
Smart pills are revolutionizing healthcare by enabling real-time monitoring and personalized interventions.
RehabCoach: Design and Evaluation for Stroke Therapy Support
RehabCoach is designed to enhance engagement and adherence to unsupervised stroke therapy through a conversational agent, showing promising usability and potential for future development.
Attribute Structuring Enhances LLM-Based Clinical Text Summaries Evaluation
Attribute Structuring improves the evaluation of clinical text summaries by utilizing LLMs for scoring attributes, leading to better alignment with human annotations.
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