In this work, a supervised learning rule based on Temporal Single Spike Coding for Effective Transfer Learning (TS4TL) is presented, an efficient approach for training multilayer fully connected Spiking Neural Networks (SNNs) as classifier blocks wit...
A brain tumor is the deadliest disease to cause sudden death, affecting billions of people worldwide. Artificial Intelligence (AI) powered technologies play a vital role in screening medical images to identify brain-suspecting tissue regions of attai...
With cardiovascular diseases accounting for all other causes of mortality worldwide, an increasing proportion of individuals are being treated for them. To identify the cardiac issue, medical practitioners have to examine electrocardiogram (ECG) data...
Fatigue creates complex challenges that present themselves through cognitive problems alongside physical impacts and emotional consequences. FatigueNet represents a modern multimodal framework that deals with two main weaknesses in present-day fatigu...
Breast cancer remains a formidable global health challenge, emphasizing the critical importance of accurate and early diagnosis for improved patient outcomes. In recent years, machine learning, particularly deep learning, has shown substantial promis...
Diabetic retinopathy is a leading cause of vision loss, necessitating early, accurate detection. Automated deep learning models show promise but struggle with the complexity of retinal images and limited labeled data. Due to domain differences, tradi...
Prostate cancer remains a leading cause of mortality, necessitating precise histopathological segmentation for accurate Gleason Grade assessment. However, existing deep learning-based segmentation models lack contextual awareness and explainability, ...
Epilepsy is one of the most prevalent neurological disorders, affecting approximately 23 million people in Asia alone. It is a disorder with severe social impacts and is going to progressively damage the brain. It encompasses a wide range of syndrome...
The gold standard for the diagnosis of sleep apnoea (SA) is polysomnography, consisting of overnight in-lab tests, which are expensive for both patients and healthcare systems. Airflow and pulse/oximetry signals contain most of the necessary informat...
Neural networks face persistent challenges in maintaining stability and robustness during training, particularly in noisy or high-dimensional domains like molecular analysis. Inspired by biological neural systems that leverage homeostasis and self-re...
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