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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Cardiology
Richa Sharma
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Electrical & Electronics Engineering Health Professions Medicine & Pharmacology

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Exploiting artificial intelligence for combating COVID-19: a review and appraisal Sharma, Richa; Pandey, Himanshu; Agarwal, Ambuj Kumar
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4366

Abstract

Machine learning algorithms immediately became critical in the battle against the COVID-19 outbreak. Diagnoses, medicine research, an illness spread predictions, and population surveillance all required the use of artificial intelligence (AI) methods as the epidemic grew in scope. To combat COVID-19, screening procedures that are both effective and rapid are required. At COVID-19, AI developers took a chance to show how AI can benefit all mankind. It was only after the employment of AI in the battle against COVID-19. AI's various and diverse applications in the epidemic are documented in this study. It is the purpose of this study to help shape the future development and usage of these technologies, whether in the present or future health crises.
Examining the Specificity of Smartphone ECG Devices in Decision-Making for ST-Elevation Myocardial Infarction and Non-ST-Elevation Myocardial Infarction mahajan, Sahil; Garg, Salil; Singh, Yogendra; sharma, richa; Bhatia, Tanuj; chandola, nitin; agarwal, deeksha
Jurnal Kardiologi Indonesia Vol 45 No 3 (2024): July - September, 2024
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1740

Abstract

Background & Objectives: Electrocardiography (ECG) stands as a cornerstone diagnostic tool for assessing cardiac health, particularly in ruling out abnormalities. The integration of smartphone devices presents a promising avenue for expedited detection of cardiac irregularities. This study aims to evaluate the diagnostic efficacy of smartphone ECG devices in subjects admitted to Cardiac Care Units (CCUs) and Cardiac Intensive Care Units (CICUs). Methods: A retrospective analysis was conducted on a cohort comprising 62 patients presenting with cardiac symptoms. Utilizing smartphone ECG devices as the index, 12-lead ECG tests were administered alongside the Gold Standard ECG machine for comparison among patients in CCUs and CICUs. Diagnostic decisions concerning the presence of ST-Elevation Myocardial Infarction (STEMI) or Non-ST-Elevation Myocardial Infarction (NSTEMI) were made by a team of cardiologists following a meticulous review of both sets of ECG reports. Results: Data analysis was conducted on 56 patients. The smartphone-based ECG device exhibited 100% specificity, 93% sensitivity, 80% Negative Predictive Value, and 100% Positive Predictive Value, yielding an F-score of 0.96 and a Mathew Correlation Coefficient value of 0.86. Discussions: This study unequivocally underscores the significant potential of the Spandan ECG device in accurately identifying a range of cardiac abnormalities, including critical conditions such as STEMI and ischemia. Despite its portable nature, smartphone ECG technology demonstrates utility within Critical Care Units for timely monitoring and diagnosis.
Co-Authors Agarwal, Ambuj Kumar agarwal, deeksha Bhatia, Tanuj chandola, nitin Garg, Salil mahajan, Sahil Pandey, Himanshu Yogendra Singh, Yogendra