A5067812665- Chronic Kidney Disease and Diabetes
- Chronic Disease Management Strategies
- Antifungal resistance and susceptibility
- Artificial Intelligence in Healthcare
- COVID-19 Clinical Research Studies
- Long-Term Effects of COVID-19
- Medical Imaging Techniques and Applications
- AI in cancer detection
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
Vellore Institute of Technology University
2020-2021
Chronic kidney disease (CKD) represents a heavy burden on the healthcare system because of increasing number patients, high risk progression to end-stage renal disease, and poor prognosis morbidity mortality. The aim this study is develop machine-learning model that uses comorbidity medication data obtained from Taiwan’s National Health Insurance Research Database forecast occurrence CKD within next 6 or 12 months before its onset, hence prevalence in population. A total 18,000 people with...
ABSTRACT Background and Objective Chronic kidney disease (CKD) represent a heavy burden on the healthcare system because of increasing number patients, high risk progression to end-stage renal disease, poor prognosis morbidity mortality. The aim this study is develop machine-learning model that uses comorbidity medication data, obtained from Taiwan's National Health Insurance Research Database, forecast whether an individual will CKD within next 6 or 12 months, thus prevalence in population....
Pneumonitis is an infectious disease that causes the inflammation of air sac. It can be life-threatening to very young and elderly. Detection pneumonitis from X-ray images a significant challenge. Early detection assistance with diagnosis crucial. Recent developments in field deep learning have significantly improved their performance medical image analysis. The superior predictive methods makes them ideal for classification chest images. However, training models cumbersome...
Abstract Introduction India reported a severe public health challenge not only due to the COVID-19 outbreak but also increasing number of associated mucormycosis cases since 2021. This study aimed at developing artificial intelligence-based models predict risk among patients time discharge from hospital. Methods The dataset included 1229 positive patients, and additional 214 inpatients, as well infected with mucormycosis. We used logistic regression, decision tree, random forest, extreme...