Electroencephalography (EEG) is widely utilized for train driver state detection due to its high accuracy and low latency. However, existing methods for driver status detection rarely use the rich physiological information in EEG to improve detection...
BACKGROUND: Developing computer-assisted methods to measure the Torg-Pavlov ratio (TPR), defined as the ratio of the sagittal diameter of the cervical spinal canal to the sagittal diameter of the corresponding vertebral body on lateral radiographs, c...
Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. Manual diagnosis is labor-intensive and prone to inaccuracies, highlighting the need for automat...
Microfluidic biosensors offer a promising solution for real-time analysis of coronaviruses with minimal sample volumes. This study optimizes a biochip for the rapid detection of SARS-CoV-2 using the Taguchi orthogonal table L(3), which comprises nine...
In deep learning, Semi-Supervised Learning is a highly effective technique to enhances neural network training by leveraging both labeled and unlabeled data. This process involves using a trained model to generate pseudo labels to the unlabeled sampl...
In this study, we explore machine learning models for predicting emotional states in ridden horses. We manually label the images to train the models in a supervised manner. We perform data exploration and use different cropping methods, mainly based ...
Elucidating the tertiary structure of proteins is important for understanding their functions and interactions. While deep neural networks have advanced the prediction of a protein's native structure from its amino acid sequence, the focus on a singl...
This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 mill...
The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains, on the other hand, are adept at learning stable sensory representations given noisy observations, a ...
Skin diseases are an important global public health issue, causing significant health and psychological burdens. Predicting dermatology outpatient visits is essential for optimizing hospital resources and improving diagnosis and treatment methods. Ba...
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