Long-term Neurological Sequelae in Post-COVID-19 Patients: A Machine Learning Approach to Predict Outcomes

by   Hayder A. Albaqer, et al.

The COVID-19 pandemic has brought to light a concerning aspect of long-term neurological complications in post-recovery patients. This study delved into the investigation of such neurological sequelae in a cohort of 500 post-COVID-19 patients, encompassing individuals with varying illness severity. The primary aim was to predict outcomes using a machine learning approach based on diverse clinical data and neuroimaging parameters. The results revealed that 68 with fatigue, headache, and anosmia being the most common manifestations. Moreover, 22 including encephalopathy and stroke. The application of machine learning models showed promising results in predicting long-term neurological outcomes. Notably, the Random Forest model achieved an accuracy of 85 80 neurological sequelae. These findings underscore the importance of continuous monitoring and follow-up care for post-COVID-19 patients, particularly in relation to potential neurological complications. The integration of machine learning-based outcome prediction offers a valuable tool for early intervention and personalized treatment strategies, aiming to improve patient care and clinical decision-making. In conclusion, this study sheds light on the prevalence of long-term neurological complications in post-COVID-19 patients and demonstrates the potential of machine learning in predicting outcomes, thereby contributing to enhanced patient management and better health outcomes. Further research and larger studies are warranted to validate and refine these predictive models and to gain deeper insights into the underlying mechanisms of post-COVID-19 neurological sequelae.


page 1

page 2

page 3

page 4

page 5

page 7

page 8

page 9


Predicting Post-Concussion Syndrome Outcomes with Machine Learning

In this paper, machine learning models are used to predict outcomes for ...

Predicting Outcomes in Long COVID Patients with Spatiotemporal Attention

Long COVID is a general term of post-acute sequelae of COVID-19. Patient...

COVID-19 Smart Chatbot Prototype for Patient Monitoring

Many COVID-19 patients developed prolonged symptoms after the infection,...

Predicting the Long-Term Outcomes of Biologics in Psoriasis Patients Using Machine Learning

Background. Real-world data show that approximately 50 treated with a bi...

Routine Outcome Monitoring in Psychotherapy Treatment using Sentiment-Topic Modelling Approach

Despite the importance of emphasizing the right psychotherapy treatment ...

Predicting special care during the COVID-19 pandemic: A machine learning approach

More than ever COVID-19 is putting pressure on health systems all around...

Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring

COVID-19 has challenged health systems to learn how to learn. This paper...

Please sign up or login with your details

Forgot password? Click here to reset