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Machine learning (ML) in medicine: review, applications, and challenges
AM Rahmani, E Yousefpoor, MS Yousefpoor… - Mathematics, 2021 - mdpi.com
Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in
various industries, especially medicine. AI describes computational programs that mimic and …
various industries, especially medicine. AI describes computational programs that mimic and …
[HTML][HTML] Innovative applications of artificial intelligence during the COVID-19 pandemic
C Lv, W Guo, X Yin, L Liu, X Huang, S Li, L Zhang - Infectious Medicine, 2024 - Elsevier
The COVID-19 pandemic has created unprecedented challenges worldwide. Artificial
intelligence (AI) technologies hold tremendous potential for tackling key aspects of …
intelligence (AI) technologies hold tremendous potential for tackling key aspects of …
Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates
(UAE) and Malaysia, emphasizing the importance of develo** accurate and reliable …
(UAE) and Malaysia, emphasizing the importance of develo** accurate and reliable …
Early detection of cognitive decline using machine learning algorithm and cognitive ability test
Elderly people are the assets of the country and the government can ensure their peaceful
and healthier life. Life expectancy of individuals has expanded with technological …
and healthier life. Life expectancy of individuals has expanded with technological …
[HTML][HTML] FedSGDCOVID: Federated SGD COVID-19 detection under local differential privacy using chest X-ray images and symptom information
Coronavirus (COVID-19) has created an unprecedented global crisis because of its
detrimental effect on the global economy and health. COVID-19 cases have been rapidly …
detrimental effect on the global economy and health. COVID-19 cases have been rapidly …
Multi-agent reinforcement learning: Methods, applications, visionary prospects, and challenges
Multi-agent reinforcement learning (MARL) is a widely used Artificial Intelligence (AI)
technique. However, current studies and applications need to address its scalability, non …
technique. However, current studies and applications need to address its scalability, non …
[Retracted] Automated System for Identifying COVID‐19 Infections in Computed Tomography Images Using Deep Learning Models
KH Abdulkareem, SA Mostafa… - Journal of healthcare …, 2022 - Wiley Online Library
Coronavirus disease 2019 (COVID‐19) is a novel disease that affects healthcare on a global
scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) …
scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) …
Harnessing deep learning and reinforcement learning synergy as a form of Strategic Energy optimization in Architectural Design: a Case Study in Famagusta, North …
This study introduces a novel framework that leverages artificial intelligence (AI), specifically
deep learning and reinforcement learning, to enhance energy efficiency in architectural …
deep learning and reinforcement learning, to enhance energy efficiency in architectural …
Symptom‐based COVID‐19 prognosis through AI‐based IoT: a bioinformatics approach
Objective. Internet of Things (IoT) integrates several technologies where devices learn from
the experience of each other thereby reducing human‐intervened likely errors. Modern …
the experience of each other thereby reducing human‐intervened likely errors. Modern …
[HTML][HTML] A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis
In the last century, the emergence of in silico tools has improved the quality of healthcare
studies by providing high quality predictions. In the case of COVID-19, these tools have …
studies by providing high quality predictions. In the case of COVID-19, these tools have …