DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology,
sleep stage scoring   deep learning   single-channel EEG   convolutional neural networks   bidirectional LSTMs   feature extraction   automation  

DeepSleepNet: An Automatic Sleep Stage Scoring Model Based on Single-Channel EEG Background Introduction Sleep has a significant impact on human health, and monitoring sleep quality is crucial in medical research and practice. Typically, sleep experts score sleep stages by analyzing various physiological signals such as electroencephalogram (EEG), ...

Vision Transformers, Ensemble Model, and Transfer Learning Leveraging Explainable AI for Brain Tumor Detection and Classification

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Oncology,
brain tumor classification   deep learning   ensemble learning   multiclass classification   transfer learning   explainable AI   vision transformers  

In recent years, due to the high incidence and lethality of brain tumors, rapid and accurate detection and classification of brain tumors have become particularly important. Brain tumors include both malignant and non-malignant types, and their abnormal growth can cause long-term damage to the brain. Magnetic Resonance Imaging (MRI) is a commonly u...

Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics from Surface EMG

Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence, Medicine, Orthopedics, Medical Laboratory Science, Medical Imaging, Life Sciences, Bioengineering,
physics-informed   deep learning   musculoskeletal modeling   EMG   muscle forces   joint kinematics  

Musculoskeletal models have been widely used in biomechanical analysis because they can estimate motion variables that are difficult to measure directly in living organisms, such as muscle forces and joint moments. Traditional physics-driven computational musculoskeletal models can explain the dynamic interactions between neural inputs to muscles, ...

Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
deep learning   real-time identification   visual learners   EEG   machine learning   electroencephalogram   classification  

In the current educational environment, understanding students’ learning styles is crucial for improving their learning efficiency. Specifically, the identification of visual learning styles can help teachers and students adopt more effective strategies in the teaching and learning process. Currently, automatic identification of visual learning sty...

Development and Validation of a Deep Learning Radiomics Model with Clinical-Radiological Characteristics for the Identification of Occult Peritoneal Metastases in Patients with Pancreatic Ductal Adenocarcinoma

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Medical Imaging, Oncology,
deep learning   radiomics   occult peritoneal metastases   pancreatic ductal adenocarcinoma   computed tomography  

Development and Validation of a Deep Learning Radiomics Model Combined with Clinical Radiological Features for Predicting Occult Peritoneal Metastasis in Patients with Pancreatic Ductal Adenocarcinoma Background Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal malignancy with a 5-year survival rate of approximately 11%. The poor progn...