The improving outcomes of coronary artery bypass graft surgery in Ontario, 1981 to 1995
Tu JV, Wu K. CMAJ. 1998; 159(3):221-7.
Publications
Predicting mortality after coronary artery bypass surgery: what do artificial neural networks learn?
Tu JV, Weinstein MC, McNeil BJ, Naylor CD; The Steering Committee of the Cardiac Care Network of Ontario. Med Decis Making. 1998; 18(2):229-35.
Fifteen-year trends in risk severity and operative mortality in elderly patients undergoing coronary artery bypass graft surgery
Ivanov J, Weisel RD, David TE, Naylor CD. Circulation. 1998; 97(7):673-80.
Assessing the outcomes of coronary artery bypass graft surgery: how many risk factors are enough?
Tu JV, Sykora K, Naylor CD. J Am Coll Cardiol. 1997; 30(5):1317-23.
Use of cardiac procedures and outcomes in elderly patients with myocardial infarction in the United States and Canada
Tu JV, Pashos CL, Naylor CD, Chen E, Normand SL, Newhouse JP, McNeil BJ. N Engl J Med. 1997; 336(21):1500-5.
Towards improved coding of acute myocardial infarction in hospital discharge abstracts: a pilot study
Cox JL, Melady MP, Chen E, Naylor CD. Can J Cardiol. 1997; 13(4):351-8.
Time to treatment with thrombolytic therapy: determinants and effect on short-term nonfatal outcomes of acute myocardial infarction
Cox JL, Lee E, Langer A, Armstrong PW, Naylor CD. CMAJ. 1997; 156(4):497-505.
Coronary artery bypass graft surgery in Ontario and New York State: which rate is right?
Tu JV, Naylor CD, Kumar D, Debuono BA, McNeil BJ, Hannan EL. Ann Intern Med. 1997; 126(1):13-9.
Coronary bypass mortality rates in Ontario: a Canadian approach to quality assurance in cardiac surgery
Tu JV, Naylor CD. Circulation. 1996; 94(10):2429-33.
Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes
Tu JV. J Clin Epidemiol. 1996; 49(11):1225-31.