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Quantitative AI based on evolutionary computation and information theory combined with mathematical functions yields algorithmic RNA biomarkers from a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient responses to anti-TNF treatment, to enable precision medicine

2024-01-30

Abstract excerpt

<h4>Background</h4> The routine derivation of novel biomarkers from therapeutic clinical trials to accurately predict individual patient’s responses, would be a significant advance. We hypothesized that quantitative AI software designed to analyze complex biomedical data, based on evolutionary computation and information theory combined with a wide range of mathematical functions, could identify algorithmic biomar...

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Literature Corpus work
5822096d-2bc6-5dd8-a7a0-2efef3d02390
DOI
10.1101/2024.01.29.24301910
Open publication

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Quantitative AI based on evolutionary computation and information theory combined with mathematical functions yields algorithmic RNA biomarkers from a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient responses to anti-TNF treatment, to enable precision medicineDOI 10.1101/2024.01.29.24301910
Quantitative AI yields algorithmic RNA biomarkers from a rheumatoid arthritis clinical trial, accurately predicting individual patient responses to anti-TNF treatment, providing a novel approach to companion diagnostic discovery.Semantic proximity
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