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Intelligent Database Systems Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin dosage from clinical data: A supervised learning approach
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Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Jan 08, 2018

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Intelligent Database Systems Lab Motivation  Physicians use computerized dosing nomograms of warfarin as reference.It merely consider age and INR values not enough for dose adjustment.
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Page 1: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Presenter : CHANG, SHIH-JIE

Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b

2012.AIM.

Predicting warfarin dosage from clinical data: A supervised learning approach

Page 2: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

OutlinesMotivationObjectivesMethodologyExperimentsConclusionsComments

Page 3: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Motivation

Physicians use computerized dosing nomograms of warfarin as reference .It merely consider age and INR values not enough for dose adjustment.

Page 4: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Objectives• Build a warfarin dosage prediction model utilizing a

number of supervised learning techniques to help dose adjustment.

Page 5: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Warfarin

Page 6: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Prediction model for warfarin dosing- Single classifiers (1) KNN

(2) SVRGiven a set of training instances

xi : input vector yi : actual output of xi

a regression function

ε-SVR can be formulated

regression hyperplane

Page 7: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Methodology - Single classifiers (3) M5 (model-tree-based regression algorithm)

use standard deviation reductionTree-building :

specific node

standard deviation of the class values of all instances in a child-node Nt,i,

Page 8: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Methodology - M5

error term

tree-pruning

Page 9: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Methodology – MLP

(4) MLP

Page 10: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Methodology – Classifier ensemble

Voting (weight)

Bagged Voting method

Decide the estimated output by combining the results of different classifiers.

Page 11: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Experiments – Data preparation Collected 587 clinical cases (INR value 1~3)

Drug-to-drug interaction (DDI)424 163

Use Bagging496

Page 12: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Experiments – Performance measures

Page 13: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Experiments – Evaluation results

Page 14: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Experiments – The average of evaluation results

Page 15: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Conclusions– The investigated models can not only facilitate

clinicians in dosage decision-making, but also help reduce patient risk from adverse drug events.

Page 16: Intelligent Database Systems Lab Presenter : CHANG, SHIH-JIE Authors : Ya-Han Hu, Fan Wu a, Chia-Lun Lo, Chun-Tien Tai b 2012.AIM. Predicting warfarin.

Intelligent Database Systems Lab

Comments• Advantages

– More accurate.• Applications

– Warfarin dosage prediction.