Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
[HTML][HTML] A comparison review of transfer learning and self-supervised learning: Definitions, applications, advantages and limitations
Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …
learning research. However, one persistent challenge is the scarcity of labelled training …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Antecedents of trustworthiness of social commerce platforms: a case of rural communities using multi group SEM & MCDM methods
Business' ethics have changed the landscape of commerce around the world lately.
Legitimacy, robustness, and morality are among the most important factors that build …
Legitimacy, robustness, and morality are among the most important factors that build …
[HTML][HTML] Generative AI in medical practice: in-depth exploration of privacy and security challenges
Y Chen, P Esmaeilzadeh - Journal of Medical Internet Research, 2024 - jmir.org
As advances in artificial intelligence (AI) continue to transform and revolutionize the field of
medicine, understanding the potential uses of generative AI in health care becomes …
medicine, understanding the potential uses of generative AI in health care becomes …
[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …
healthcare, enabling a comprehensive understanding of patient health and personalized …
Explainable artificial intelligence (XAI): concepts and challenges in healthcare
T Hulsen - AI, 2023 - mdpi.com
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally
require human intelligence, such as visual perception, speech recognition, decision-making …
require human intelligence, such as visual perception, speech recognition, decision-making …
What is machine learning, artificial neural networks and deep learning?—Examples of practical applications in medicine
Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all
topics that fall under the heading of artificial intelligence (AI) and have gained popularity in …
topics that fall under the heading of artificial intelligence (AI) and have gained popularity in …
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
[HTML][HTML] A systematic review of trustworthy artificial intelligence applications in natural disasters
AS Albahri, YL Khaleel, MA Habeeb, RD Ismael… - Computers and …, 2024 - Elsevier
Artificial intelligence (AI) holds significant promise for advancing natural disaster
management through the use of predictive models that analyze extensive datasets, identify …
management through the use of predictive models that analyze extensive datasets, identify …