Implantable Medical Devices (IMDs) have revolutionized the treatment of critical diseases. However, the increasing reliance on these life-saving devices’ wireless functionality has made them vulnerable to cyber-attac...
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In the swiftly advancing domain of healthcare informatics, the exigency for intricately sophisticated and meticulously calibrated information retrieval systems has attained a critical juncture. This paper elucidates t...
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Blockchain technology is widely recognized for its ability to secure data integrity and confidentiality in a trustless environment, safeguarding against cyber threats. Organizations face challenges in distinguishing p...
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The pandemic has a significant impact on how people conduct meetings, both in corporations and in schools. Online meetings have become a popular way to connect people from all over the world, lowering the expenses and...
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Sustainability is a long-term commitment. Businesses must measure their environmental impact regularly if they wish to be environmentally friendly in the long run. Determining true ecological impact is difficult, maki...
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Epilepsy, a neurological disorder characterized by recurrent seizures, poses significant challenges in timely intervention and patient safety, affecting millions of individuals worldwide. Early and accurate detection ...
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This paper aims to establish a comprehensive analysis of mental health patient reviews using various NLP models, to derive insights and propose improvements that will lead to the enhancement of various mental health f...
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The ubiquitous use of social media impacts the social life of humans. Fake news negatively affects a person's behavior. Fake news detection in social media has been a challenging problem for the last decade. Resea...
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One of the fast-growing disease affecting women’s health seriously is breast *** is highly essential to identify and detect breast cancer in the earlier *** paper used a novel advanced methodology than machine learni...
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One of the fast-growing disease affecting women’s health seriously is breast *** is highly essential to identify and detect breast cancer in the earlier *** paper used a novel advanced methodology than machine learning algorithms such as Deep learning algorithms to classify breast cancer *** learning algorithms are fully automatic in learning,extracting,and classifying the features and are highly suitable for any image,from natural to medical *** methods focused on using various conventional and machine learning methods for processing natural and medical *** is inadequate for the image where the coarse structure matters *** of the input images are downscaled,where it is impossible to fetch all the hidden details to reach accuracy in *** deep learning algorithms are high efficiency,fully automatic,have more learning capability using more hidden layers,fetch as much as possible hidden information from the input images,and provide an accurate *** this paper uses AlexNet from a deep convolution neural network for classifying breast cancer in mammogram *** performance of the proposed convolution network structure is evaluated by comparing it with the existing algorithms.
Digital Twins replicate the real situations and the outcomes, helping organizations to make better decisions. Digital Twins find valuable in different domains such as manufacturing, automotive, healthcare, and etc. In...
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