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Current Review and Next Steps for Artificial Intelligence in Multiple Sclerosis Risk Research by Morghan Hartmann; Norman Fenton; Ruth Dobson is a Medicine article available to read on EtoBox.

What is Current Review and Next Steps for Artificial Intelligence in Multiple Sclerosis Risk Research about?

In the last few decades, the prevalence of multiple sclerosis (MS), a chronic inflammatory disease of the nervous system, has increased, particularly in Northern European countries, the United States, and United Kingdom. The promise of artificial intelligence (AI) and machine learning (ML) as tools to address problems in MS research has attracted increasing interest in these methods. Bayesian networks offer a clear advantage since they can integrate data and causal knowledge allowing for visualizing interactions between dependent variables and potential confounding factors. A review of AI/ML research methods applied to MS found 216 papers using terms "Multiple Sclerosis", "machine learning", "artificial intelligence", "Bayes", and "Bayesian", of which 90 were relevant and recently published. More than half of these involve the detection and segmentation of MS lesions for quantitative analysis; however clinical and lifestyle risk factor assessment and prediction have largely been ignored. Of those that address risk factors, most provide only association studies for some factors and often fail to include the potential impact of confounding factors and bias (especially where these hav

Who reads Current Review and Next Steps for Artificial Intelligence in Multiple Sclerosis Risk Research?

Author

Morghan Hartmann; Norman Fenton; Ruth Dobson

Publisher

Elsevier BV

Published

2021

Language

EN

Field

Medicine (Physical Sciences)