Modèles de prédiction du risque cardio-vasculaire
Validation et évaluation de modèles
Publication du groupe projet sur les données INDANA
Goodman P and Harrell Fj, NevProp Manual with Introduction to Artificial
Neural Network Theory, http://www.unr.nevada.edu/~goodman/nevprop/ or
http://brain.unr.edu/FILES_PHP/show_papers.php, (last access on february 2002).
Goodman PH and Rosen DB, NevProp software, version 4r1.,
http://www.unr.nevada.edu/~goodman/nevprop/ or
http://brain.unr.edu/FILES_PHP/show_papers.php, (last access on february 2002).
Anderson KM, Odell PM, Wilson PW, and Kannel WB, Cardiovascular
disease risk profiles. Am Heart J, 1991. 121(1 Pt 2):293-8.
Anderson KM, Wilson PW, Odell PM, and Kannel WB, An updated coronary
risk profile. A statement for health professionals. Circulation,
1991. 83(1):356-62.
Baker S, Priest P, and Jackson R, Using thresholds based on risk of
cardiovascular disease to target treatment for hypertension: modelling events
averted and number treated. BMJ, 2000. 320(7236):680-5.
Baxt WG, Application of artificial neural networks to clinical
medicine. Lancet, 1995. 346(8983):1135-8.
Baxt WG and Skora J, Prospective validation of artificial neural
network trained to identify acute myocardial infarction. Lancet, 1996. 347(8993):12-5.
D'Agostino RB, Sr., Grundy S, Sullivan LM, and Wilson P, Validation
of the Framingham coronary heart disease prediction scores: results of a
multiple ethnic groups investigation. JAMA, 2001. 286(2):180-7.
D'Agostino RB, Russell MW, Huse DM, et al., Primary and subsequent
coronary risk appraisal: new results from the framingham study. Am Heart J,
2000. 139(2 Pt 1):272-81.
D'Agostino RB, Wolf PA, Belanger AJ, and Kannel WB, Stroke risk
profile: adjustment for antihypertensive medication. The Framingham Study. Stroke,
1994. 25(1):40-3.
Kennedy RL, Harrison RF, Burton AM, et al., An artificial neural
network system for diagnosis of acute myocardial infarction (AMI) in the
accident and emergency department: evaluation and comparison with serum
myoglobin measurements. Comput Methods Programs Biomed, 1997. 52(2):93-103.
Knuiman MW, Vu HT, and Segal MR, An empirical comparison of
multivariable methods for estimating risk of death from coronary heart disease.
J Cardiovasc Risk, 1997. 4(2):127-34.
Kubat M, Holte R, and Matwin S. Learning when negative examples
abound. in European Conference Machine Learning (ECML). 1997.
Lapuerta P, Azen PS, and LaBree L, Use of neural networks in
predicting the risk of coronary artery disease. Comp Biomed Res., 1995. 28:38-52.
Lapuerta P, L'Italien GJ, Paul S, et al., Neural network assessment
of perioperative cardiac risk in vascular surgery patients. Med Decis
Making, 1998. 18(1):70-5.
Pocock SJ, McCormack V, Gueyffier F, et al., A score for predicting risk of
death from cardiovascular disease in adults with raised blood pressure, based
on individual patient data from randomised controlled trials. BMJ, 2001. 323(7304):75-81.
Segal MR and Bloch DA, A comparison of estimated proportional hazards
models and regression trees. Stat Med, 1989. 8(5):539-50.
Selker HP, Griffith JL, Patil S, Long WJ, and D'Agostino RB, A
comparison of performance of mathematical predictive methods for medical
diagnosis: identifying acute cardiac ischemia among emergency department
patients. J Investig Med, 1995. 43(5):468-76.
Silver DL and Hurwitz GA, The predictive and explanatory power of
inductive decision trees: a comparison with artificial neural network learning
as applied to the noninvasive diagnosis of coronary artery disease. J Investig Med, 1997. 45(2):99-108.
Tu JV, Weinstein MC, McNeil BJ, Naylor D, et al. Predicting mortality after coronary
artery bypass surgery: what do artificial neural networks learn ? Med Decis Making, 1998. 18:229-35.
Concato J, Feinstein AR, and Holford TR, The risk of determining risk
with multivariable models. Ann Intern Med, 1993. 118(3):201-10.
Diamond GA, What price perfection? Calibration and discrimination of
clinical prediction models. J Clin Epidemiol, 1992. 45(1):85-9.
Hanley JA and McNeil BJ, The meaning and use of the area under a
receiver operating characteristic (ROC) curve. Radiology, 1982. 143(1):29-36.
Hanley JA and McNeil BJ, A method of comparing the areas under
receiver operating characteristic curves derived from the same cases. Radiology,
1983. 148(3):839-43.
Harrell FE, Jr., Lee KL, and Mark DB, Multivariable prognostic
models: issues in developing models, evaluating assumptions and adequacy, and
measuring and reducing errors. Stat Med, 1996. 15(4):361-87.
Heckerling PS, Conant RC, Tape TG, and Wigton RS, Discrimination and
reproducibility of an information maximizing multivariable model. Methods
Inf Med, 1993. 32(2):131-6.
Justice AC, Covinsky KE, and Berlin JA, Assessing the
generalizability of prognostic information. Ann Intern Med, 1999. 130(6):515-24.
Laupacis A, Sekar N, and Stiell IG, Clinical prediction rules. A
review and suggested modifications of methodological standards. JAMA, 1997.
277(6):488-94.
Leaverton PE, Sorlie PD, Kleinman JC, et al., Representativeness of
the Framingham risk model for coronary heart disease mortality: a comparison
with a national cohort study. J Chronic Dis, 1987. 40(8):775-84.
McGinn TG, Guyatt GH, Wyer PC, et al., Users' guides to the medical
literature: XXII: how to use articles about clinical decision rules. Evidence-Based
Medicine Working Group. Jama, 2000. 284(1):79-84.
Raubertas RF, Rodewald LE, Humiston SG, and Szilagyi PG, ROC curves
for classification trees. Med Decis Making, 1994. 14(2):169-74.
Wald NJ, Hackshaw AK, and Frost CD, When can a risk factor be used as
a worthwhile screening test? BMJ, 1999. 319(7224):1562-1565. (télécharger)
Zaragoza H and D'Alché-Buc F. Confidence measure for neural network
classifiers. in IPMU'98. 1998. Paris.
Colombet I, Ruelland A, Chatellier G, et al., Models to predict
cardiovascular risk: comparison of CART, multilayer perceptron and logistic
regression. Proc AMIA Symp, 2000:156-60.
Gueyffier F, Boutitie F, Boissel JP, et al., INDANA: a meta-analysis
on individual patient data in hypertension. Protocol and
preliminary results. Therapie, 1995. 50(4):353-62.
Gueyffier F, Boutitie F, Boissel JP, et al., Effect of antihypertensive
drug treatment on cardiovascular outcomes in women and men. A meta-analysis of
individual patient data from randomized, controlled trials. The INDANA Investigators.
Ann Intern Med, 1997. 126(10):761-7.