A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana.

ABSTRACT:

Background

Snakebite envenoming is a serious condition that affects 2.5 million people and causes 81,000-138,000 deaths every year, particularly in tropical and subtropical regions. The World Health Organization has set a goal to halve the deaths and disabilities related to snakebite envenoming by 2030. However, significant challenges in achieving this goal include a lack of robust research evidence related to snakebite incidence and treatment, particularly in sub-Saharan Africa. This study aimed to combine established methodologies with the latest tools in Artificial Intelligence to assess the barriers to effective snakebite treatment in Ghana.

Method

We used a MaxDiff statistical experiment design to collect data, and six supervised machine learning models were applied to

SUBMITTER: Nyarko E 

PROVIDER: S-EPMC11676561 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature