Applying artificial neural network models to clinical decision making

Psychological Assessment

Volumn 12, Issue 1, 2000, Pages 40-51

  Price, Rumi Kato ^b   Downey, Thomas J ^a   Meyer, Donald J ^a   Spitznagel, Edward L ^c   Risk, Nathan K ^c   El Ghazzawy, Omar G ^c  

^a Partek Inc   (United States)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COMPUTER ASSISTED DIAGNOSIS; HUMAN; MEDICAL DECISION MAKING; PSYCHIATRIC DIAGNOSIS; PSYCHOLOGIC ASSESSMENT; REVIEW; STATISTICAL MODEL;

EID: 0343527317     PISSN: 10403590     EISSN: None     Source Type: Journal    
DOI: 10.1037/1040-3590.12.1.40     Document Type: Review

References (78)

1. Achen, C. (1982). Interpreting and using regression. In J. L. Sullivan & R. G. Niemi (Series Eds.), Sage University paper series on quantitative applications in the social sciences (07-001). Beverly Hills, CA: Sage.
2. American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). Washington, DC: Author.
3. American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: Author.
4. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.
5. Anderer, P., Saletu, B., Klöppel, B., Semlitsch, H. V., & Werner, H. (1994). Discrimination between demented patients and normals based on topographic EEG slow wave activity: Comparison between Z statistics, discriminant analysis, and artificial neural network classifiers. Electroencephalography and Clinical Neurophysiology, 91, 108-117.
6. Anderson, J. A. (1995). An introduction to neural networks. Cambridge, MA: MIT Press.
7. Baxt, W. G. (1995). Application of artificial neural networks to clinical medicine. Lancet, 346, 1135-1138.
8. Berrios, G. E., & Chen, E. Y. H. (1993). Recognizing psychiatric symptoms. Relevance to the diagnostic process. British Journal of Psychiatry, 163, 308-314.
9. Bishop, C. M. (1995). Neural networks for pattern recognition. Oxford, England: Oxford University Press.
10. Chen, E. Y. H. (1994). A neural network model of cortical information processing in schizophrenia. I: Interaction between biological and social factors in symptom formation. Canadian Journal of Psychiatry, 39, 362-367.
11. Cheng, B., & Titterington, D. M. (1994). Neural networks: A review from a statistical perspective. Statistical Science, 9, 2-54.
12. Davis, G. E., Walter, E. L., & Davis, G. L. (1993). A neural network that predicts psychiatric length of stay. Clinical Computing, 10, 87-92.
13. De Laurentiis, M., & Ravdin, P. M. (1994). Survival analysis of censored data: Neural network analysis detection of complex interaction between variables. Breast Cancer Research and Treatment, 32, 113-118.
14. Doig, G. S., Inman, K. J., Sibbald, W. J., Martin, C. M., & Robertson, J. M. (1994). Modeling mortality in the intensive care unit: Comparing the performance of a back-propagation, associative-learning network with multivariate logistic regression. Proceedings of the Annual Symposium on Computer Applications in Medical Care, 361-365.
15. Downey, T. J., & Meyer, D. J. (1994). A genetic algorithm for feature selection. In C. H. Dagli, B. R. Fernandes, J. Ghosh, & R. T. S. Kumura (Eds.), Intelligent engineering systems through artificial neural networks (Vol. 4, pp. 363-369). New York: ASME Press.
16. Duh, M. S., Walker, A. M., & Ayanian, J. Z. (1998). Epidemiologic interpretation of artificial neural networks. American Journal of Epidemiology, 147, 1112-1122.
17. Duh, M. S., Walker, A. M., Pagano, M., & Kronlund, K. (1998). Prediction and cross-validation of neural networks versus logistic regression: Using hepatic disorders as an example. American Journal of Epidemiology, 147, 407-413.
18. Dwyer, C. A. (1996). Cut scores and testing: Statistics, judgment, truth, and error. Psychological Assessment, 8, 360-362.
19. Dybowski, R., Weller, P., Chang, R., & Gant, V. (1996). Prediction of outcome in critically ill patients using artificial neural network synthesized by genetic algorithm. Lancet, 347, 1146-1150.
20. Eaton, W. W., & Kessler, L. G. (Eds.). (1985). Epidemiologic field methods in psychiatry: The NIMH Epidemiologic Catchment Area Program. Orlando, FL: Academic Press.
21. Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14, 179-211.
22. Erdreich, L. S., & Lee, E. T. (1981). Use of relative operating characteristic analysis in epidemiology. A method for dealing with subjective judgement. American Journal of Epidemiology, 14, 649-662.
23. Fahlman, S. E. (1989). Faster-learning variations on back-propagation: An empirical study. In D. Touretzky, G. Hinton, & T. Sejnowski (Eds.), Proceedings of the 1988 Connectionist Models Summer School (pp. 38-51). San Mateo, CA: Morgan Kaufmann.
24. Fu, H. C., & Shann, J. (1994). A fuzzy neural network for knowledge learning. International Journal of Neural System, 5, 13-22.
25. Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Reading, MA: Addison-Wesley.
26. Gonzalez-Heydrich, J. (1993). Using neural networks to model personality development. Medical Hypotheses, 41, 123-130.
27. Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143, 29-36.
28. Hastie, T. J., & Tibshirani, R. J. (1990). Generalized additive models. London: Chapman & Hall.
29. Helzer, J. E., Stoltzman, R. K., Farmer, A., Brockington, I. F., Plesons, D., Singerman, B., & Works, J. (1985). Comparing the DIS with a DIS/DSM-III-based physician reevaluation. In W. W. Eaton & L. G. Kessler (Eds.), Epidemiologic field methods in psychiatry: The NIMH Epidemiologic Catchment Area Program (pp. 285-308). Orlando, FL: Academic Press.
30. Herjanic, B., & Reich, W. (1982). Development of a structured psychiatric interview for children: Agreement between child and parent on individual symptoms. Journal of Abnormal Child Psychology, 10, 307-324.
31. Ioannidis, J. P. A., McQueen, P. G., Goedert, J. J., & Kaslow, R. A. (1998). Use of neural networks to model complex immunogenetic associations of disease: Human leukocyte antigen impact on the progression of human immunodeficiency virus infection. American Journal of Epidemiology, 147, 464-471.
32. Kashani, J. H., Nair, S. S., Rao, V. G., Nair, J., & Reid, J. C. (1996). Relationship of personality, environmental and DICA variables to adolescent hopelessness: A neural network sensitivity approach. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 640-645.
33. Kuzin, I. A. (1995). Hypnotic modeling in neural networks. Bulletin on Mathematical Biology, 57, 1-20.
34. Lette, J. L., Colletti, B., Cerino, M., McNamara, D., Eybalin, M. C., Levasseur, A., & Nattel, S. (1994). Artificial intelligence versus logistic regression statistical modeling to predict cardiac complications after noncardiac surgery. Clinical Cardiology, 17, 609-614.
35. Liestøl, K., Andersen, P. K., & Andersen, U. (1994). Survival analysis and neural nets. Statistics in Medicine, 13, 1189-1200.
36. Loeber, R. (1988). Natural histories of conduct problems, delinquency, and associated substance use. Evidence for developmental progressions. In B. B. Lahey & A. E. Kazdin (Eds.), Advances in clinical child psychology (Vol. 11, pp. 73-124). New York: Plenum Press.
37. Lowell, W. E., & Davis, G. E. (1994). Predicting length of stay for psychiatric diagnosis-related groups using neural networks. Journal of the American Medical Informatics Association, 6, 459-466.
38. Lucek, P. R., & Ott, J. (1997). Neural network analysis of complex traits. Genetic Epidemiology, 14, 1101-1106.
39. McCulloch, W. S., & Pitts, W. (1943). A logical calculus of ideas immanent in nervous activity. Bulletin on Mathematical Biophysics, 5, 115-133.
40. Modai, I., Stoler, M., Inbar-Saban, N., & Saban, N. (1993). Clinical decisions for psychiatric inpatients and their evaluation by a trained neural network. Methods of Information in Medicine, 32, 396-399.
41. O'Donnell, J. A., Voss, H. L., Clayton, R. R., Slatin, G. T., & Room, R. G. W. (1976). Young men and drugs - Nationwide survey (NIDA Research Monograph No. 5; DHEW Publication No. ADM 76-311). Springfield, VA: National Institute on Drug Abuse. (NTIS No. PB 247-446)
42. Palombo, S. R. (1992). Connectivity and condensation in dreaming. Journal of the American Psychoanalytic Association, 40, 1139-1159.
43. Partek, Inc. (1998). Partek: Pattern Analysis and Recognition Technology (Version 2.0B7) [Computer software]. St. Peters, MO: Author.
44. Phelps, C. E., & Hutson, L. (1995). Estimating diagnostic test accuracy using a "fuzzy gold standard." Medical Decision Making, 15, 44-57.
45. Price, R. K., Eisen, S. A., Virgo, K. S., Murray, K. S., & Robins, L. N. (1995). Vietnam drug users two decades later. I. Mortality results [Abstract]. In Proceedings of the 56th Annual Scientific Meeting of the College on Problems of Drug Dependence, Inc. (Vol. 2, p. 204; NIDA Research Monograph No. 153; DHHS Publication No. NIH95-3883). Washington, DC: U.S. Government Printing Office.
46. Price, R. K., Risk, N. K., & Spitznagel, E. L. (1999). Remission from illicit drug use over a 24-year period. Part I. Patterns and predictors of remission and treatment use. Manuscript submitted for publication.
47. Price, R. K., Risk, N. K., Stwalley, D., Murray, K. S., Eisen, S., Virgo, K. S., Spitznagel, E. L., & Robins, L. N. (1999). Vietnam drug users twenty-five years later. Patterns and early predictors of mortality. Manuscript submitted for publication.
48. Price, R. K., Robins, L. N., Helzer, J. E., & Cottler, L. B. (1998). Examining the internal validity of DSM-III and -III-R symptom criteria for substance dependence and abuse. In T. Widiger & A. Frances (Eds.), DSM-IV source book (Vol. 4, pp. 51-68). Washington, DC: American Psychiatric Press.
49. Prochaska, J. O., & DiClemente, C. C. (1983). Stages and process of self-change in smoking: Toward an integrative model of change. Journal of Consulting and Clinical Psychology, 5, 390-395.
50. Ralston, M. L., & Jennrich, R. I. (1978). Dud, a derivative-free algorithm for nonlinear least squares. Technometrics, 20, 7-14.
51. Reid, J. C., Nair, S. S., Mistry, S. I., & Beitman, B. D. (1996). Effectiveness of stages of change and adinazolam SR in panic disorder: A neural network analysis. Journal of Anxiety Disorders, 10, 331-345.
52. Ripley, B. D. (1994). Comment to "Neural networks: A review from a statistical perspective." Statistical Science, 9, 45-48.
53. Ripley, B. D. (1996). Pattern recognition and neural networks. Cambridge, England: Cambridge University Press.
54. Robins, L. N. (1974). The Vietnam drug user returns (Special Action Office Monograph, Series A, No. 2). Washington, DC: U.S. Government Printing Office.
55. Robins, L. N., & Helzer, J. E. (1975). Drug use among Vietnam veterans -three years later. Medical World News - Psychiatry, 16, 44-49.
56. Robins, L. N., Helzer, J. E., Croughan, J., & Ratcliff, K. S. (1981). The NIMH Diagnostic Interview Schedule: Its history, characteristics, and validity. Archives of General Psychiatry, 38, 381-389.
57. Robins, L. N., Helzer, J. E., & Davis, D. H. (1975). Narcotic use in Southeast Asia and afterward: An interview study of 898 Vietnam returnees. Archives of General Psychiatry, 32, 955-961.
58. Robins, L. N., Helzer, J. E., Ratcliff, K. S., & Seyfried, W. (1982). Validity of the Diagnostic Interview Schedule, Version II: DSM-III diagnoses. Psychological Medicine, 12, 855-870.
59. Robins, L. N., & Price, R. K. (1991). Adult disorders predicted by childhood conduct problems: Results from the Epidemiologic Catchment Area Program. Psychiatry, 54, 116-132.
60. Robins, L. N., & Regier, D. A. (Eds.). (1991). Psychiatric disorders in America. New York: Free Press.
61. Robins, L. N., Wing, J., Wittchen, H. U., Helzer, J. E., Babor, T. F., Burke, J., Farmer, A., Jablenski, A., Pickens, R., Regier, D. A., Sartorius, N., & Towle, L. H. (1988). The composite international diagnostic interview. Archives of General Psychiatry, 45, 1069-1077.
62. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533-536.
63. Rumelhart, D. E., & McClelland, J. L. (Eds.). (1986). Parallel distributed processing: Explorations in the microstructure of cognition: Vol. 1. Foundations. Cambridge, MA: MIT Press.
64. Sarle, W. S. (1994, April). Neural networks and statistical models. In Proceedings of the 19th Annual SAS Users Group International Conference, Cary, NC.
65. Sarle, W. S. (1996, June). Comp.ai.neural-nets FAQ [7 parts]. Usenet newsgroup comp.ai.neural-nets. Available FTP: ftp://ftp.sas.com/pub/ neural/FAQ.html.
66. So, S-S., & Karplus, M. (1996). Evolutionary optimization in qualitative structure - Activity relationship: An application of genetic neural networks. Journal of Medical Chemistry, 39, 1521-1530.
67. Somoza, E., & Somoza, J. R. (1993). A neural-network approach to predicting admission decisions in a psychiatric emergency room. Medical Decision Making, 13, 273-280.
68. Spackman, K. A. (1992). Combining logistic regression and neural networks to create predictive models. In Proceedings of the Annual Symposium on Computer Applications in Medical Care, 456-459.
69. Swets, J. A., & Pickett, R. M. (1982). Evaluation of diagnostic systems: Methods from signal detection theory. New York: Academic Press.
70. U.S. General Accounting Office. (1998). Drug abuse - Research shows treatment is effective, but benefits may be overstated (Report to congressional requesters; GAO/HEHS-98-72). Washington, DC: U.S. Government Printing Office.
71. Warner, B., & Misra, M. (1996). Understanding neural networks as statistical tools. American Statistician, 50, 284-293.
72. Weinstein, M. C., & Fineberg, H. V. (1980). Clinical decision analysis. Philadelphia: W.B. Saunders.
73. White, H. (1989). Learning in artificial neural networks: A statistical perspective. Neural Computation, 1, 425-464.
74. White, H. (1992). Artificial neural networks: Approximation and learning theory. Oxford, England: Blackwell.
75. Wiles, J., & Bloesch, A. (1992). Operators and curried functions: Training and analysis of simple recurrent networks. In J. E. Moddy, S. J. Hansen, & R. P. Lippman (Eds.), Advances in neural information processing systems 4 (pp. 325-332). San Mateo, CA: Morgan Kaufmann.
76. Wu, Y. C., & Gustafson, D. H. (1994). Removing the assumption of conditional independence from Bayesian decision models by using artificial neural networks: Some practical techniques and a case study. Artificial Intelligence in Medicine, 6, 437-454.
77. Zou, Y., Shen, Y., Shu, L., Wang, Y., Feng, F., Xu, K., Qu, Y., Song, Y., Zhong, Y., Wang, M., & Liu, W. (1996). Artificial neural networks to assist psychiatric diagnosis. British Journal of Psychiatry, 169, 64-67.
78. Zurada, J. M. (Ed.). (1992). Introduction to artificial neural systems. St. Paul, MN: West Publishing.