Smartphone addiction among students has emerged as a critical issue, negatively impacting their academic performance, emotional well-being, and social behavior. This paper introduces the Theory of Mind integrated with Video Modelling (TMVM) framework...
Abortion is a critical health issue that leads to numerous complications, maternal deaths, and significant financial burdens on women, families, and healthcare systems. Studies have identified factors associated with abortion using traditional statis...
Bladder cancer diagnosis is a challenging task because of its intricacy and variation of tumor features. Moreover, morphological similarities of the cancerous cells make manual diagnosis time-consuming. Recently, machine learning and deep learning me...
Over the years, toxicity prediction has been a challenging task. Artificial intelligence and machine learning provide a platform to study toxicity prediction more accurately with a reduced time span. An optimized ensembled model is used to contrast t...
This study is aimed to clarify the effectiveness of the image-rotation technique and zooming augmentation to improve the accuracy of the deep learning (DL)-based dose conversion from pencil beam (PB) to Monte Carlo (MC) in proton beam therapy (PBT). ...
Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accurate risk stratification. However, existing machine learning models for sepsis prediction often suffer from poor interpretability, limited generalizab...
Current brain tumor segmentation methods often utilize a U-Net architecture based on efficient convolutional neural networks. While effective, these architectures primarily model local dependencies, lacking the ability to capture global interactions ...
The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient c...
Chronic kidney disease is a persistent ailment marked by the gradual decline of kidney function. Its classification primarily relies on the estimated glomerular filtration rate and the existence of kidney damage. The kidney disease improving global o...
This article introduces a novel deep-learning based framework, Super-resolution/Denoising network (SDNet), for simultaneous denoising and super-resolution of swept-source optical coherence tomography (SS-OCT) images. The novelty of this work lies in ...
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