Cognizance of Post-COVID-19 Multi-Organ Dysfunction through Machine
  Learning Analysis
Hector J. Castro Maitham G. Yousif
In the year 2022, a total of 466 patients from various cities across Iraq
were included in this study. This research paper focuses on the application of
machine learning techniques to analyse and predict multi-organ dysfunction in
individuals experiencing Post-COVID-19 Syndrome, commonly known as Long COVID.
Post-COVID-19 Syndrome presents a wide array of persistent symptoms affecting
various organ systems, posing a significant challenge to healthcare. Leveraging
the power of artificial intelligence, this study aims to enhance early
detection and management of this complex condition. The paper outlines the
importance of data collection and preprocessing, feature selection and
engineering, model development and validation, and ethical considerations in
conducting research in this field. By improving our understanding of
Post-COVID-19 Syndrome through machine learning, healthcare providers can
identify at-risk individuals and offer timely interventions, potentially
improving patient outcomes and quality of life. Further research is essential
to refine models, validate their clinical utility, and explore treatment
options for Long COVID. Keywords: Post-COVID-19 Syndrome, Machine Learning,
Multi-Organ Dysfunction, Healthcare, Artificial Intelligence.