ML Odinschool Project for diagnosis of COVID-19
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most individuals infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. However, older adults and those with underlying medical conditions such as cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop severe illness.
Throughout the pandemic, one of the primary challenges faced by healthcare providers has been the shortage of medical resources and the lack of an effective plan for their efficient distribution. In these challenging times, the ability to predict the specific resources an individual might require upon testing positive, or even prior to testing, would be immensely beneficial. Such predictive capabilities would enable authorities to procure and arrange the necessary resources, thereby improving patient outcomes and potentially saving lives.
Goal: This project aims to predict COVID-19 diagnoses based on symptoms and demographic data, utilizing data analysis and machine learning techniques.
Methodology: We employ Python and MySQL for data analysis, exploratory data analysis (EDA), feature engineering, and machine learning to predict COVID-19 outcomes.
Why: Our project is crucial for early COVID-19 detection, efficient healthcare resource allocation, and informed public health decision-making, ultimately improving overall well-being.
Q1 . Why is your proposal important in today’s world? How predicting a disease accurately can improve medical treatment?
ANS : Accurately predicting diseases using machine learning, particularly for COVID-19, is highly significant in today’s world. Early detection based on symptoms enables healthcare facilities to isolate and treat patients promptly, which is crucial for preventing the spread of the disease.
Q2. How is it going to impact the medical field when it comes to effective screening and reducing health care burden.
ANS: Impact on Medical Facilities: Currently, medical facilities use tests such as the Rapid Antigen Test (RAT) to detect COVID-19. Our machine learning model leverages patient data to accurately determine COVID-19 infection, significantly reducing the burden of testing and screening on healthcare facilities.
Q3. If any, what is the gap in the knowledge or how your proposed method can be helpful if required in future for any other disease.
ANS: Future Applications: Poor-quality or missing data can pose challenges for these models. However, if our model proves effective for COVID-19, similar approaches could be applied to other diseases in the future, providing a valuable tool for medical facilities.