External Validation of a Thiopurine Monitoring Algorithm on the SONIC Clinical Trial Dataset
暂无分享,去创建一个
P. Higgins | Ji Zhu | A. Waljee | Yiwei Zhang | K. Sauder
[1] P. Higgins,et al. Machine Learning Algorithms for Objective Remission and Clinical Outcomes with Thiopurines , 2017, Journal of Crohn's & colitis.
[2] Lisa Rosenbaum,et al. Bridging the Data-Sharing Divide - Seeing the Devil in the Details, Not the Other Camp. , 2017, The New England journal of medicine.
[3] Christopher F. Martin,et al. Randomised clinical trial: individualised vs. weight‐based dosing of azathioprine in Crohn's disease , 2014, Alimentary pharmacology & therapeutics.
[4] Akbar K Waljee,et al. Machine Learning in Medicine: A Primer for Physicians , 2010, The American Journal of Gastroenterology.
[5] P. Rutgeerts,et al. Infliximab, azathioprine, or combination therapy for Crohn's disease. , 2010, The New England journal of medicine.
[6] Sijian Wang,et al. Algorithms outperform metabolite tests in predicting response of patients with inflammatory bowel disease to thiopurines. , 2010, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.
[7] V. Armstrong,et al. 6-thioguanine nucleotide-adapted azathioprine therapy does not lead to higher remission rates than standard therapy in chronic active crohn disease: results from a randomized, controlled, open trial. , 2007, Clinical chemistry.
[8] J. Lewis,et al. Association of 6-thioguanine nucleotide levels and inflammatory bowel disease activity: a meta-analysis. , 2006, Gastroenterology.