An artificial intelligence based study to evaluate the association between Covid infection or vaccination on heart diseases

A comparative evaluation of six sigma metrics and quality goal index ratio 3 months prior to first lockdown due to COVID-19 pandemic and 3 months during lockdown in a NABL accredited central laboratory

Introduction and Aim: Sigma represents Standard Deviation (SD) which indicates the degree of variation in a process, where the higher sigma value implies that less likely the laboratory reports false test results. Using a newer parameter called Quality Goal Index (QGI) we can find the reason behind the lower sigma value. Our study aimed to compare the six-sigma metric and QGI ratio 3 months prior to first lockdown due to COVID-19 pandemic and 3 months during the first lockdown. Methodology: A retrospective study was used to compare the six-sigma metric and QGI ratio 3 months prior to first lockdown due to COVID-19 pandemic and 3 months during the first lockdown for the selected ten analytes from 1st of January 2020 to 30th of June 2020 from the clinical biochemistry section of Yenepoya Medical College Hospital, Deralakatte, Mangalore. Result(s): The sigma metrics from January to March (level 1) indicated that urea, TSH, beta-HCG fell short of meeting Six Sigma quality performance and from April to June, glucose, creatinine, urea and ALT had metrics less than 3 at both the Internal Quality Control levels. QGI ratio indicated that from January to March, the problem was imprecision for urea, TSH and beta-HCG (QGI < 0.8). From April to June, urea and creatinine showed imprecision, glucose and ALT showed inaccuracy, urea and ALT showed both imprecision and inaccuracy. Conclusion(s): This study highlights the necessity for stringent Internal Quality Control and External Quality Assurance monitoring even during the lockdown period of the pandemic. By implementing six sigma and finding QGI ratio, quality of laboratory services can be improved immensely. Copyright © 2022, Indian Association of Biomedical Scientists. All rights reserved.

Role of Artificial Intelligence in COVID-19 Detection.

The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.