Clinician face value validation of SVM and PDCA for endotype classification.

<p>This figure presents the face value validation of the predicted T2D endotypes by SVM and PDCA using a subset cohort of 450 individuals, classified into four groups: SIDD (severe insulin-deficient diabetes), IROD (insulin-resistant obese diabetes), CIRDD (combined insulin-resistant and defic...

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Main Author:	Viswanathan Baskar (1782799) (author)
Other Authors:	Mani Arun Vignesh (21989338) (author), Sumanth C. Raman (21989341) (author), Arun Jijo (21989344) (author), Bhavadharini Balaji (21989347) (author), Nico Steckhan (8213514) (author), Lena Maria Klara Roth (21989350) (author), Moneeza K. Siddiqui (6882965) (author), Saravanan Jebarani (15474443) (author), Ranjit Unnikrishnan (561908) (author), Viswanathan Mohan (239503) (author), Ranjit Mohan Anjana (9402612) (author)
Published:	2025
Subjects:	Biochemistry Medicine Genetics Molecular Biology Biotechnology Marine Biology Cancer Plant Biology Virology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified support vector machine make informed decisions provide precision management shapley additive explanations random forest model predict endotype membership machine learning model asian indian population type 2 diabetes relatively high accuracy individual &# 8217 vs 73 %, algorithm determined based precision values compared 6 %, 99 svm model reported endotype prediction model precision compared 1 %, svm model determined cut asian indians agnostic explanations &# 8211 trained based vs 66 vs 65 vs 63 related diabetes obese diabetes deficient diabetes individual risk xlink "> t2d subgroups study demonstrated predict individuals peptide stimulated peptide fasting ml models mard ). irod ), fold cross conditional pre clinical feature
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Clinician face value validation of SVM and PDCA for endotype classification.

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