Home Project Analysing and identifying COVID-19 risk factors using machine learning algorithm with smartphone application.

Analysing and identifying COVID-19 risk factors using machine learning algorithm with smartphone application.

This study is divided into risk factor analysis (RFA) and proposed system architecture (PSA). The light gradient boosting machine (LightGBM) algorithm in the RFA will work with the PSA to predict the risk factors. The results, efficacy, and performance will be validated via a ROC-AUC curve. Therefore, a system usability scale (SUS) procedure will be implemented to increase the performance. If the...

Machine Learning, Android Application, Light Gradient Boosting Machine (LightGBM), System Usability Scale (SUS), Risk Factors Component.

We have designed the modules for identifying risk factors of COVID-19, and these modules worked perfectly, incorporating the smartphone application.

Who we've worked with

Portsmouth University, UK

Portsmouth University, UK

Team member of this project

Shah Siddiqui

Shah Siddiqui

Founder and CEO of Timerni

Elias Hossain

Elias Hossain

Senior Resarcher (AI/ML)

S. M. Asaduzzaman

S. M. Asaduzzaman

Research Manager (Data Scientist)

Wahidur Rahman

Wahidur Rahman

Senior Researcher (Journal & Publications)

Dr Shamsul Masum

Dr Shamsul Masum

Advisor Of System & e-learning

Prof. Adrian Hopgood

Prof. Adrian Hopgood

Chief of Advisory Board (Global)

Dr Alice Good

Dr Alice Good

Advisor of Applied Science Research

Dr Alexander Gegov

Dr Alexander Gegov

Advisor of Intelligence Science

Collaborator of this project

Sponsor of this project