AIMC Topic: Adult

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Feature extraction method of EEG based on wavelet packet reconstruction and deep learning model of VR motion sickness feature classification and prediction.

PloS one
The surging popularity of virtual reality (VR) technology raises concerns about VR-induced motion sickness, linked to discomfort and nausea in simulated environments. Our method involves in-depth analysis of EEG data and user feedback to train a soph...

The SSHVEP Paradigm-Based Brain Controlled Method for Grasping Robot Using MVMD Combined CNN Model.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In recent years, the steady-state visual evoked potentials (SSVEP) based brain control method has been employed to help people with disabilities because of its advantages of high information transmission rate and low training time. However, the exist...

Detection and severity assessment of obstructive sleep apnea according to deep learning of single-lead electrocardiogram signals.

Journal of sleep research
Developing a convenient detection method is important for diagnosing and treating obstructive sleep apnea. Considering availability and medical reliability, we established a deep-learning model that uses single-lead electrocardiogram signals for obst...

Artificial Intelligence Portrayals in Orthopaedic Surgery: An Analysis of Gender and Racial Diversity Using Text-to-Image Generators.

The Journal of bone and joint surgery. American volume
BACKGROUND: The increasing accessibility of artificial intelligence (AI) text-to-image generators offers a novel avenue for exploring societal perceptions. The present study assessed AI-generated images to examine the representation of gender and rac...

Development, validation, and usability evaluation of machine learning algorithms for predicting personalized red blood cell demand among thoracic surgery patients.

International journal of medical informatics
INTRODUCTION: Preparing appropriate red blood cells (RBCs) before surgery is crucial for improving both the efficacy of perioperative workflow and patient safety. In particular, thoracic surgery (TS) is a procedure that requires massive transfusion w...

Machine/deep learning-assisted hemoglobin level prediction using palpebral conjunctival images.

British journal of haematology
Palpebral conjunctival hue alteration is used in non-invasive screening for anaemia, whereas it is a qualitative measure. This study constructed machine/deep learning models for predicting haemoglobin values using 150 palpebral conjunctival images ta...

A machine-learning approach for stress detection using wearable sensors in free-living environments.

Computers in biology and medicine
Stress is a psychological condition resulting from the body's response to challenging situations, which can negatively impact physical and mental health if experienced over prolonged periods. Early detection of stress is crucial to prevent chronic he...

Comparison of automated deep neural network against manual sleep stage scoring in clinical data.

Computers in biology and medicine
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines.

A Deep Transfer Learning Approach for Sleep Stage Classification and Sleep Apnea Detection Using Wrist-Worn Consumer Sleep Technologies.

IEEE transactions on bio-medical engineering
Obstructive sleep apnea (OSA) is a common, underdiagnosed sleep-related breathing disorder with serious health implications Objective - We propose a deep transfer learning approach for sleep stage classification and sleep apnea (SA) detection using w...

ECGAN-Assisted ResT-Net Based on Fuzziness for OSA Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: Growing attention has been paid recently to electrocardiogram (ECG) based obstructive sleep apnea (OSA) detection, with some progresses been made on this topic. However, the lack of data, low data quality, and incomplete data labeling hind...