Artificial neural network-based pharmacogenomic algorithm for warfarin dose optimization

To develop more precise pharmacogenomic algorithm for prediction of safe and effective dose of warfarin. An artificial neural network (ANN) algorithm was developed by using age, gender, BMI, plasma vitamin K levels, thyroid status and ten genetic variables as the inputs and therapeutic warfarin dose...

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Veröffentlicht in:	Pharmacogenomics 2016-01, Vol.17 (2), p.121-131
Hauptverfasser:	Pavani, Addepalli, Naushad, Shaik Mohammad, Kumar, Rajasekar Manoj, Srinath, Murali, Malempati, Amaresh Rao, Kutala, Vijay Kumar
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Algorithms Anticoagulants Anticoagulants - administration & dosage Anticoagulants - chemistry Anticoagulants - pharmacokinetics artificial neural networks Bioinformatics Cytochrome Cytochrome P-450 CYP2C9 - genetics Dosage Drug dosages Female Haplotypes Humans Hypothyroidism Male Metabolism Middle Aged Models, Biological Neural networks Neural Networks (Computer) Patients Pharmacogenomics Polymorphism Regression analysis Stereoisomerism Thyroid Thyroid gland Vitamin K Warfarin Warfarin - administration & dosage Warfarin - chemistry Warfarin - pharmacokinetics warfarin/7-OH warfarin ratio Young Adult
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