Neural network and linear regression models in residency selection

American Journal of Emergency Medicine

Volumn 15, Issue 4, 1997, Pages 361-364

  Pilon, Steve ^a   Tandberg, Dan ^a  

^a UNIVERSITY OF NEW MEXICO SCHOOL OF MEDICINE   (United States)

Author keywords

Educational measurement; Emergency medicine; Internship and residency; Neural networks; Resident selection

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER MODEL; PRIORITY JOURNAL; REGRESSION ANALYSIS; RESIDENCY EDUCATION; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 0030848289     PISSN: 07356757     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0735-6757(97)90125-X     Document Type: Article

References (23)

1. McCabe JB: Computer-aided ranking of residency program applicants. J Med Educ 1983;58:656-657
2. Gordon MJ, Lincoln JA: Selecting a few residents from many applicants: A new way to be fair and efficient. J Med Educ 1976;51: 454-460
3. Wagoner NE, Gray GT: Report on a survey of program directors regarding selection factors in graduate medical education. J Med Educ 1979;54:445-452
4. Hughes RL, Golmon ME, Patterson R: The grading system as a factor in the selection of residents. J Med Educ 1983:58:479-481
5. Wagoner NE, Suriano JR, Stoner JA: Factors used by program directors to select residents. J Med Educ 1986;61:10-21
6. Aghababian R, Tandberg D, Iserson K, Martin M, Sklar D: Selection of emergency medicine residents. Ann Emerg Med 1993;22: 1753-1761
7. Bond A, Lader M: The use of analogue scales in rating subjective feelings. Br J Med Psychol 1974;47:211-218
8. Rice JA: Mathematical Statistics and Data Analysis. Pacific Grove, CA, Wadsworth & Brooks/Cole Advanced Book & Software, 1988
9. van Camp D: Neurons for computers. Scientific American 1992;September:170-172
10. Hinton GE: How neural networks learn from experience. Scientific American 1992;September:145-151
11. Rumelhart DE, McClelland JL: Parallel Distributed Processing - Explorations in the Microstructure of Cognition. Cambridge, MA, The MIT Press, 1986
12. Obermeir KK, Barron JJ: Time to get fired up. Byte 1989;August: 217-224
13. Kohonen T: An introduction to neural computing. Neural Networks 1988:1:3-16
14. Guerriere MRJ, Detsky AS: Neural networks: What are they? Ann Intern Med 1991;115:906-907
15. Baxt WG: Use of an artificial neural network for the diagnosis of myocardial infarction. Ann Intern Med 1991;115:843-848
16. Tu JV, Guerriere MRJ: Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Comput Biomed Res 1993;26:220-229
17. Eberhart RC, Dobbins RW, Hutton LV: The use of neural networks for appendicitis diagnoses. Computer-Based Medical Systems: Proceedings of the Fourth Annual IEEE Symposium, Baltimore, MD, May 12-14, 1991. Los Alamitos, CA, IEEE Computer Society Press, 1991
18. Kohonen T: The self-organizing map. Proceedings of the IEEE 1990;78:1464-1480
19. Carpenter GA, Grossberg S: ART 2: Self-organization of stable category recognition codes for analog input patterns. Appl Optics 1987;26:4919-4930
20. Lawrence M, Lawrence J: Brainmaker Professional User's Guide and Reference Manual (ed 3). Nevada City, CA, California Scientific Software, 1992
21. Nemiroff PM, King DC: Group decision-making performance as influenced by consensus and self-orientation. Human Relations 1975;28:1-21
22. Kendall M, Stuart A, Ord JK: Tests of hypotheses in multivariate analysis. In The Advanced Theory of Statistics (ed 4). London & High Wyncombe, UK, Charles Griffin & Co, 1983, pp 295-319
23. Wilks SS: Sample criteria for testing equality of means, equality of variances and equality of covariances in a normal multivariate distribution. Ann Math Statist 1946:17:257-281