Optimized Ensemble Machine Learning Model for Chronic Kidney Disease Prediction

C Choudhary, LS Nagra, P Das, J Singh… - 2023 International …, 2023 - ieeexplore.ieee.org
The prevalence of chronic kidney illness has been increasing by a rate of 41.5 over the past
few years, posing a significant challenge for healthcare systems worldwide. The disease is …

The Multi-Class Detection of Five Stages of Hepatitis C using the Machine Learning based Random Forest Algorithm

SA Farooq - 2023 World Conference on Communication & …, 2023 - ieeexplore.ieee.org
Hepatitis C is a viral illness that primarily impacts the liver, inducing persistent inflammation
and potentially resulting in significant liver harm over an extended duration. Its transmission …

Exploring Regression Models and Optimization Techniques for Accurate Body Fat Prediction: A Comparative Approach

A Kunwar, S Pandey, A Pandey… - 2024 4th International …, 2024 - ieeexplore.ieee.org
Globally a lot of individuals are currently struggling with the issue of obesity, this study
explores the fascinating subject of body fat prediction while examining the complex world of …

The prediction of hairfall pattern in a person using artificial intelligence for better care and treatment

SA Farooq, A Ali, A Bashir - 2024 4th International Conference …, 2024 - ieeexplore.ieee.org
Alopecia, also known as hair loss, is a term used to describe hair loss from the scalp or other
parts of the body. It can be caused by a number of factors, such as genetics, hormonal …

Applying Reinforcement Learning to Optimize Treatment Plans for Chronic Disease Management

G Saranya, K Sivaraman - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
Effective treatment regimens are necessary for the long-term management of chronic
illnesses, which burden healthcare systems globally. This study investigates using …

Machine learning-based optimisation of ultra-brief questionnaires for mental health disorders

D Glavin - 2024 - researchrepository.ul.ie
Machine learning (ML) is capable of identifying patterns in vast amounts of data that humans
cannot identify as easily. Given this capability, researchers have begun investigating the use …

A Ensemble Learning Based Stacking Technique to Train a Cleaned Diabetes Dataset

AS Bhuyan, SA Farooq… - … Conference on Artificial …, 2023 - ieeexplore.ieee.org
Diabetes which is believed to be a lengthy and brutal ailment that disrupts the normal blood
sugar ranges for a human body, necessitating diligent monitoring and lifestyle adaptations …