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Research on Emotion Recognition of EEG Signal Based on Convolutional Neural Networks and High-Order Cross-Analysis.

Journal of healthcare engineering
Emotion recognition means the automatic identification of a human's emotional state by obtaining his/her physiological or nonphysiological signals. The EEG-based method is an effective mechanism, which is commonly used for the recognition of emotions...

Automated Cardioailment Identification and Prevention by Hybrid Machine Learning Models.

Computational and mathematical methods in medicine
Accurate prediction of cardiovascular disease is necessary and considered to be a difficult attempt to treat a patient effectively before a heart attack occurs. According to recent studies, heart disease is said to be one of the leading origins of de...

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.

Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study.

Journal of Korean medical science
BACKGROUND: Videofluoroscopic swallowing study (VFSS) is currently considered the gold standard to precisely diagnose and quantitatively investigate dysphagia. However, VFSS interpretation is complex and requires consideration of several factors. The...

Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography.

Scientific reports
Determining the exact positional relationship between mandibular third molar (M3) and inferior alveolar nerve (IAN) is important for surgical extractions. Panoramic radiography is the most common dental imaging test. The purposes of this study were t...

Predictive classification of Alzheimer's disease using brain imaging and genetic data.

Scientific reports
For now, Alzheimer's disease (AD) is incurable. But if it can be diagnosed early, the correct treatment can be used to delay the disease. Most of the existing research methods use single or multi-modal imaging features for prediction, relatively few ...

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

Acta neuropathologica communications
The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized th...

A novel lifelong machine learning-based method to eliminate calibration drift in clinical prediction models.

Artificial intelligence in medicine
OBJECTIVE: Clinical prediction models (CPMs) constructed based on artificial intelligence have been proven to have positive impacts on clinical activities. However, the deterioration of CPM performance over time has rarely been studied. This paper pr...

Effectiveness of Retzius-Sparing Robot-Assisted Radical Prostatectomy in a Renal Transplant Recipient: a Case Report.

Transplantation proceedings
BACKGROUND: Prostate cancer (PCa) has increased as a long-term outcome of advanced immunosuppression in renal transplant recipients (RTRs). Retzius-sparing robot-assisted radical prostatectomy (Rs-RARP) is reportedly less time-consuming and has a hig...

Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI.

Nature communications
To help doctors and patients evaluate lumbar intervertebral disc degeneration (IVDD) accurately and efficiently, we propose a segmentation network and a quantitation method for IVDD from T2MRI. A semantic segmentation network (BianqueNet) composed of...