AIMC Topic: Deep Learning

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Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...

Exploring Multiple Application Scenarios of Visual Communication Course Using Deep Learning Under the Digital Twins.

Computational intelligence and neuroscience
The emergence of intelligent technology has brought a particular impact and allows for virtuality-reality interaction in the educational field. In particular, digital twins (DTs) feature virtuality-reality symbiosis, solid virtual simulation, and hig...

Anatomical Partition-Based Deep Learning: An Automatic Nasopharyngeal MRI Recognition Scheme.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Training deep learning (DL) models to automatically recognize diseases in nasopharyngeal MRI is a challenging task, and optimizing the performance of DL models is difficult.

Heuristic-based channel selection with enhanced deep learning for heart disease prediction under WBAN.

Computer methods in biomechanics and biomedical engineering
The main intention of this proposal is to design and develop a new heart disease prediction model via WBAN using three stages. The first stage is data aggregation, in which data is scheduled in Time Division Multiple Access manner based on priority l...

Automatic detection and classification of peri-prosthetic femur fracture.

International journal of computer assisted radiology and surgery
PURPOSE: Object classification and localization is a key task of computer-aided diagnosis (CAD) tool. Although there have been numerous generic deep learning (DL) models developed for CAD, there is no work in the literature to evaluate their effectiv...

Deep learning model using retinal vascular images for classifying schizophrenia.

Schizophrenia research
Contemporary psychiatric diagnosis still relies on the subjective symptom report of the patient during a clinical interview by a psychiatrist. Given the significant variability in personal reporting and differences in the skill set of psychiatrists, ...

High-Frequency Ultrasound Dataset for Deep Learning-Based Image Quality Assessment.

Sensors (Basel, Switzerland)
This study aims at high-frequency ultrasound image quality assessment for computer-aided diagnosis of skin. In recent decades, high-frequency ultrasound imaging opened up new opportunities in dermatology, utilizing the most recent deep learning-based...

Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances.

Sensors (Basel, Switzerland)
Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the...

Evaluations of Deep Learning Approaches for Glaucoma Screening Using Retinal Images from Mobile Device.

Sensors (Basel, Switzerland)
Glaucoma is a silent disease that leads to vision loss or irreversible blindness. Current deep learning methods can help glaucoma screening by extending it to larger populations using retinal images. Low-cost lenses attached to mobile devices can inc...

Deep Learning Capabilities for the Categorization of Microcalcification.

International journal of environmental research and public health
Breast cancer is the most common cancer in women worldwide. It is the most frequently diagnosed cancer among women in 140 countries out of 184 reporting countries. Lesions of breast cancer are abnormal areas in the breast tissues. Various types of br...