AIMC Topic: Humans

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An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network.

IEEE transactions on bio-medical engineering
OBJECTIVE: Attention decoding plays a vital role in daily life, where electroencephalography (EEG) has been widely involved. However, training a universally effective model for everyone is impractical due to substantial interindividual variability in...

Extracorporeal Closed-Loop Respiratory Regulation for Patients With Respiratory Difficulty Using a Soft Bionic Robot.

IEEE transactions on bio-medical engineering
OBJECTIVE: Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alt...

Characterizing the Coefficient of Friction Between a Capsule Robot and the Colon.

IEEE transactions on bio-medical engineering
OBJECTIVE: A capsule robot (CR) with an onboard active locomotion mechanism, has been developed as a promising alternative to colonoscopy due to its minimally-invasive advantage. Predicting the traction force and locomotion resistance of the CR, whic...

Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B  ∼  50 mT) MRI.

Application Value of a Machine Learning Model in Predicting Mild Depression Associated with Migraine without Aura.

British journal of hospital medicine (London, England : 2005)
To investigate the application value of a machine learning model in predicting mild depression associated with migraine without aura (MwoA). 178 patients with MwoA admitted to the Department of Neurology of the First Affiliated Hospital of Anhui Un...

Comparison of Faster R-CNN, YOLO, and SSD for Third Molar Angle Detection in Dental Panoramic X-rays.

Sensors (Basel, Switzerland)
The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing AI information from different sensor data such as images or panoramic radiographs (panoramic X-rays) can help to improve medic...

Inferring ECG Waveforms from PPG Signals with a Modified U-Net Neural Network.

Sensors (Basel, Switzerland)
There are two widely used methods to measure the cardiac cycle and obtain heart rate measurements: the electrocardiogram (ECG) and the photoplethysmogram (PPG). The sensors used in these methods have gained great popularity in wearable devices, which...

Efficacy of robot-assisted gait training on lower extremity function in subacute stroke patients: a systematic review and meta-analysis.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-Assisted Gait Training (RAGT) is a novel technology widely employed in the field of neurological rehabilitation for patients with subacute stroke. However, the effectiveness of RAGT compared to conventional gait training (CGT) in im...

Surface and deep learning: a blended learning approach in preclinical years of medical school.

BMC medical education
BACKGROUND: Significant challenges are arising around how to best enable peer communities, broaden educational reach, and innovate in pedagogy. While digital education can address these challenges, digital elements alone do not guarantee effective le...

Deep radiomics-based prognostic prediction of oral cancer using optical coherence tomography.

BMC oral health
BACKGROUND: This study aims to evaluate the integration of optical coherence tomography (OCT) and peripheral blood immune indicators for predicting oral cancer prognosis by artificial intelligence.