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ChatGPT and Artificial Intelligence in Hospital Level Research: Potential, Precautions, and Prospects.

Methodist DeBakey cardiovascular journal
Rapid advancements in artificial intelligence (AI) have revolutionized numerous sectors, including medical research. Among the various AI tools, OpenAI's ChatGPT, a state-of-the-art language model, has demonstrated immense potential in aiding and enh...

Learning Skill Training Schedules From Domain Experts for a Multi-Patient Multi-Robot Rehabilitation Gym.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A robotic gym with multiple rehabilitation robots allows multiple patients to exercise simultaneously under the supervision of a single therapist. The multi-patient training outcome can potentially be improved by dynamically assigning patients to rob...

Automated Patient-Robot Task Assignment in a Simulated Stochastic Rehabilitation Gym.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Rehabilitation after neurological injury can be provided by robots that help patients perform different exercises. Multiple such robots can be combined in a rehabilitation robot gym to allow multiple patients to perform a diverse range of exercises s...

Robot assisted Fetoscopic Laser Coagulation: Improvements in navigation, re-location and coagulation.

Artificial intelligence in medicine
Fetoscopic Laser Coagulation (FLC) for Twin to Twin Transfusion Syndrome is a challenging intervention due to the working conditions: low quality images acquired from a 3 mm fetoscope inside a turbid liquid environment, local view of the placental su...

Accurate Monitoring of 24-h Real-World Movement Behavior in People with Cerebral Palsy Is Possible Using Multiple Wearable Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Monitoring and quantifying movement behavior is crucial for improving the health of individuals with cerebral palsy (CP). We have modeled and trained an image-based Convolutional Neural Network (CNN) to recognize specific movement classifiers relevan...

MAG-Res2Net: a novel deep learning network for human activity recognition.

Physiological measurement
Human activity recognition (HAR) has become increasingly important in healthcare, sports, and fitness domains due to its wide range of applications. However, existing deep learning based HAR methods often overlook the challenges posed by the diversit...

[Establishment of comprehensive evaluation models of physical fitness of the elderly based on machine learning].

Sheng li xue bao : [Acta physiologica Sinica]
The present study aims to establish comprehensive evaluation models of physical fitness of the elderly based on machine learning, and provide an important basis to monitor the elderly's physique. Through stratified sampling, the elderly aged 60 years...

Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App: A Content Analysis.

Health education & behavior : the official publication of the Society for Public Health Education
In the field of artificial intelligence-based fitness apps, the effective integration of behavior change techniques (BCTs) is critical for promoting physical activity and improving health outcomes. However, the specific BCTs employed by apps and thei...

Intelligent Millimeter-Wave System for Human Activity Monitoring for Telemedicine.

Sensors (Basel, Switzerland)
Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, an...