Application of bayesian classifier for the diagnosis of dental pain

Journal of Medical Systems

Volumn 36, Issue 3, 2012, Pages 1425-1439

  Chattopadhyay, Subhagata ^a   Davis, Rima M ^b   Menezes, Daphne D ^b   Singh, Gautam ^b   Acharya, Rajendra U ^c   Tamura, Toshio ^d  

^a NATIONAL INSTITUTE OF SCIENCE AND TECHNOLOGY   (India)

^b MANIPAL INSTITUTE OF TECHNOLOGY   (India)

^c DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING   (Singapore)

^d CHIBA UNIVERSITY   (Japan)

Author keywords

Bayesian classifier; Dental pain; Hill climbing algorithm; Learning rate; Regressions

Indexed keywords

ANALYSIS OF VARIANCE; ANALYTICAL EQUIPMENT; ARTICLE; BAYESIAN CLASSIFIER; CONTROLLED STUDY; DENTIST; DIAGNOSTIC ACCURACY; MULTIPLE LINEAR REGRESSION ANALYSIS; PAIN PARAMETERS; QUESTIONNAIRE; RELIABILITY; TOOTH PAIN;

ALGORITHMS; BAYES THEOREM; DIAGNOSTIC TECHNIQUES AND PROCEDURES; HUMANS; QUESTIONNAIRES; TOOTHACHE;

EID: 84864069808     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-010-9604-y     Document Type: Article

References (42)

1. Kiani, M., and Sheikhazadi, A., A five-year survey for dental malpractice claims in Tehran, Iran. J. Forensic Leg. Med. 16 (2):76-82, 2009.
2. Tversky, A., and Kahneman, D., Judgment under uncertainty: Heuristics and Biases Amos Tversky. Sci. New Ser. 85 (4157):1124-1131, 1974.
3. Shortliffe, E. H., and Cimino, J. J., Biomedical informaticscomputer applications in health care and biomedicine, 3rd edition. Springer, New York, 2006.
4. Locker, D., and Grushka, M., Prevalence of oral and facial pain and discomfort: Preliminary results of a mail survey. Community Dent. Oral Epidemiol. 15(3):169-172, 1987.
5. Borra, R. C., Andrade, P. M., Corrêa, L., and Novelli, M. D., Development of an open case-based decision-support system for diagnosis in oral pathology. Eur. J. Dent. Educ. 11(2):87-92, 2007.
6. White, S. C., Decision-support systems in dentistry. J. Dent. Educ. 60(1):47-63, 1996.
7. Raab, W. H., Acute and chronic toothache. Dtsch Zahnärztl. Z. 46 (2):101-108, 1991.
8. Paris, M., Trunde, F., Bossard, D., Farges, J. C., and Coudert, J. L., Dental ankylosis diagnosed by CT with tridimensional reconstructions. J. Radiol. 91(6):707-711, 2010.
9. Cunha-Cruz, J., Wataha, J. C., Zhou, L., Manning, W., Trantow, M., Bettendorf, M. M., et al., J. Am. Dent. Assoc. 141(9):1097-1105, 2010.
10. Khan, J., Heir, G. M., and Quek, S. Y., Cerebellopontine angle (CPA) tomor mimicking dental pain following facial trauma. Cranio 28(3):205-208, 2010.
11. Weisleder, R., Yamauchi, S., Caplan, D. J., Trope, M., and Teixeira, F. B., The validity of pulp testing: A clinical study. J. Am. Dent. Assoc. 140(8):1013-1017, 2009.
12. Firriolo, F. J., and Wang, T., Diagnosis of selected pulpal pathoses using an expert computer system. Oral Surg. Oral Med. Oral Pathol. 76(3):390-396, 1993.
13. Umar, H., Capabilities of computerized clinical decision support systems: The implications for the practicing dental professional. J. Contemp. Dent. Pract. 3(1):27-42, 2002.
14. Rudin, J. L., DART (Diagnostic Aid and Resource Tool): A computerized clinical decision support system for oral pathology. Compend. 15(11):1316, 1318, 1320, 1994.
15. Mercer, P. E., and Ralph, J. P., Computer-assisted learning and the general dental practitioner. Br. Dent. J. 184(1):43-46, 1998. (Pubitemid 128529479)
16. Ralls, S. A., Cohen, M. E., and Southard, T. E., Computer-assisted dental diagnosis. Dent. Clin. North Am. 30(4):695-712, 1986.
17. Zhizhina, N. A., Prokhonchukov, A. A., Balashov, A. N., and Pelkovskiǐ, V Iu, The DIAST automated computer system for the differential diagnosis and treatment of periodontal diseases. Stomatologiia (Mosk.) 76(6):50-55, 1997.
18. Grigg, P., and Stephens, C. D., Computer-assisted learning in dentistry a view from the UK. J. Dent. 26(5-6):387-395, 1998.
19. Araki, K., Matsuda, Y., Seki, K., and Okano, T., Effect of computer assistance on observer performance of approximal caries diagnosis using intraoral digital radiography. Clin. Oral Investig. 14(3):319-325, 2010.
20. deDombal, F. T., Leaper, D. J., Staniland, J. R., McCann, A. P., and Horrock, J. C., Computer-aided diagnosis of acute abdominal pain. BMJ 2:9-13, 1972.
21. Cooper, G. F., and Herskovits, E., A Bayesian method for the induction of probabilistic networks from data. Mach. Learn. 9 (4):309-347, 1992.
22. Berry, D. A., Bayesian statistics and the efficiency and ethics of clinical trials. Stat. Sci. 19(1):175-187, 2004. (Pubitemid 39056885)
23. Tan, S. B., Introduction to Bayesian methods for medical research. Ann. Acad. Med. Singapore 30:445, 2001.
24. Stojadinovic, A., Peoples, G. E., Libutti, S. K., Henry, L. R., Eberhardt, J., Howard, R. S., et al., Development of a clinical decision model for thyroid nodules. BMC Surg. 9:12, 2009.
25. Nissan, A., Protic, M., Bilchik, A., Eberhardt, J., Peoples, G. E., and Stojadinovic, A., Predictive model of outcome of targeted nodal assessment in colorectal cancer. Ann. Surg. 251 (2):265-274, 2010.
26. Gilthorpe, M. S., Maddick, I. H., and Petrie, A., Introduction to Bayesian modelling in dental research. Community Dent. Health 17(4):218, 2000.
27. Nieri, M., Rotundo, R., Franceschi, D., Cairo, F., Cortellini, P., and Prato, G. P., Factors affecting the outcome of the coronally advanced flap procedure: A Bayesian network analysis. J. Periodontol. 80(3):405-410, 2009.
28. Mago,V. K., Prasad, B., Bhatia, A., andMago, A., A decision making system for the treatment of dental caries, in Soft computing applications in business, Prasad B. (Ed.) Vol. 230. Springer, Berlin, pp. 231-242, 2008.
29. Bandyopadhyay, D., Reich, B. J., and Slate, E. H., Bayesian modeling of multivariate spatial binary data with applications to dental caries. Stat. Med. 28(28):3492-3508, 2009.
30. Komarek, A., Lesaffre, E., Harkanen, T., Declerck, D., and Virtanen, J. I., A Bayesian analysis of multivariate doublyinterval-censored dental data. Biostatistics 6(1):145-155, 2005. (Pubitemid 41240375)
31. Nie, N., Bent, D. H., and Hull, C. H., Statistical package for the social sciences, McGraw-Hill. Eds 1 & 2, 1970, 1975.
32. Taylor, G. W., Manz, M. C., and Borgnakke, W. S., Diabetes, periodontal diseases, dental caries, and tooth loss: A review of the literature. Compend. Contin. Educ. Dent. 25(3):179-184, 2004.
33. Pihlstrom, B. L., Michalowicz, B. S., and Johnson, N. W., Periodontal diseases. Lancet 366(9499):1809-1820, 2005. (Pubitemid 41642647)
34. Cronbach, L. J., Coefficient alpha and the internal structure of tests. Psychometrika 16(3):297-334, 1951.
35. Santos, J. R. A., Cronbach's alpha: A tool for assessing the reliability of scales. J. Ext. 37(2), 1999.
36. Han J., and Kamber M., Data mining: concepts and techniques. Morgan Kaufmann Publishers, 2006.
37. Wong, M. C. M., Lam, K. F., and Lo, E. C. M., Bayesian analysis of clustered interval-censored data. J. Dent. Res. 84 (9):817-821, 2005. (Pubitemid 43827813)
38. Russell, S., and Norvig, P., Artificial Intelligence: A Modern Approach (3rd. edition). Pearson Prentice Hall, 2009.
39. Rosenbrock, H. H., An automatic method for finding the greatest or least value of a function. Comput. J. 3(3):175-184, 1960.
40. Campbell, M. J., and Gardner, M. J., Statistics in medicine: Calculating confidence intervals for some non-parametric analyses. Br. Med. J. 296(6634):1454-1456, 1988.
41. Antony, J., Pros and cons of Six Sigma: An academic perspective. TQM Mag. 16(4):303-306, 2004. (Pubitemid 41143994)
42. Carlin, B. P., and Louis, T. A., Bayes and empirical bays methods for data analysis. J. Stat. Comput. 7(2):153-154, 1997.