Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment

Abstract

Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats. In this study, the most recent related publications, methodologies and medical reports were investigated with the purpose of studying artificial intelligence’s role in the pandemic. This study presents a comprehensive review of artificial intelligence with specific attention to machine learning, deep learning, image processing, object detection, image segmentation, and few-shot learning studies that were utilized in several tasks related to COVID-19. In particular, genetic analysis, medical image analysis, clinical data analysis, sound analysis, biomedical data classification, socio-demographic data analysis, anomaly detection, health monitoring, personal protective equipment (PPE) observation, social control, and COVID-19 patients’ mortality risk approaches were used in this study to forecast the threatening factors of COVID-19. This study demonstrates that artificial-intelligence-based algorithms integrated into Internet of Things wearable devices were quite effective and efficient in COVID-19 detection and forecasting insights which were actionable through wide usage. The results produced by the study prove that artificial intelligence is a promising arena of research that can be applied for disease prognosis, disease forecasting, drug discovery, and to the development of the healthcare sector on a global scale. We prove that artificial intelligence indeed played a significantly important role in helping to fight against COVID-19, and the insightful knowledge provided here could be extremely beneficial for practitioners and research experts in the healthcare domain to implement the artificial-intelligence-based systems in curbing the next pandemic or healthcare disaster.

Challenges and solutions in clinical research during the COVID‐19 pandemic: A narrative review

“…An example of such a disease is the seasonal Flu. From this perspective, many AI approaches (including disease forecasting, surveillance, expected peak, and spread models) have been proposed and developed for several diseases, including the seasonal flu, which is relatively similar in its symptoms to COVID‐19 64 …”

“…From this perspective, many AI approaches (including disease forecasting, surveillance, expected peak, and spread models) have been proposed and developed for several diseases, including the seasonal flu, which is relatively similar in its symptoms to COVID-19. 64 There was also a need for an international committee of statistical experts to decide on statistical methods during the COVID-19 pandemic. 33,71 Additional measures were needed besides the usual strategies for conducting a clinical trial to deal with the mentioned challenges in a pandemic.…”

“…21,30 • Quality of publication during COVID-19. 31 • Refusals and losses of follow-up 32 • Research in a special population 26,47 • Accessing to epidemiological data for collecting data 25,43 • Artificial intelligence and deep learning algorithm in analysis 21,25 • Adapting statistical methods to the pandemic conditions 64 • Reduction the number of face-to-face visits 7,15,51 • Visits are conducted remotely or via phone or video call 7,14 • Mailing drug to the participants 47 and sending the medicine directly to the patient's home by site personnel or sponsors 20,63 • Using volunteer registry for enrolment of patients 18 • Making strong communication and commitment to participants 52 • Creatingtechnologicalcapabilitiesforteleworking, 34 visits 35,47 • Motivating to perform procedures at the patient's home 63 • Permitting-use, healthcare facilities, 65 3.3 | Administrative issues (REC or IRB approval)…”

Harnessing artificial intelligence in the post-COVID-19 era: A global health imperative

“…6 These AI tools showed superiority over ordinary computer technology through their ability to analyze and draw insights from vast amounts of data quickly, identifying trends and predictions more accurately. 7 Yet, the broader implementation of AI encounters substantial challenges. Notably, the digital divide, with AI applications primarily concentrated in high-income countries, undermines collective security, and exacerbates health inequities.…”

A Systematic Review and Analysis on Deep Learning Techniques Used in Diagnosis of Covid-19

“…The suggested model had a low complexity AUC-ROC of 0.79. Hasan et al [26] This paper focuses on how artificial intelligence might help battle the COVID-19 epidemic. AI-based algorithms incorporated into wearable technology were successful in detecting and anticipating COVID-19.…”