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Lanjanian, H.
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Lanjanian, H.
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Evaluating machine learning-powered classification algorithms which utilize variants in the GCKR gene to predict metabolic syndrome: Tehran Cardio-metabolic Genetics Study
by
Akbarzadeh, M.
,
Alipour, N.
,
Azizi, F.
,
Daneshpour, M.S
,
Hosseini-Esfahani, F.
,
Lanjanian
,
H
.
,
Moheimani, H.
,
Zahedi, A.S
Published 2022
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Related Subjects
Adaptor Proteins, Signal Transducing
Algorithms
Decision tree
Discriminant analysis
GCKR protein, human
Humans
Iran
Logistic Models
Logistic Regression
Machine Learning
Metabolic Syndrome
Metabolic syndrome
Random Forest
Support Vector Machine
Support vector machines
algorithm
genetics
human
machine learning
metabolic syndrome X
signal transducing adaptor protein
statistical model
support vector machine
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