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constructor-igor / MedicalApi

Medical API feasibility
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review the algorithm "Context-Sensitive Support" #11

Open victor-prp opened 7 years ago

victor-prp commented 7 years ago

A Context-Sensitive Support System for Medical Diagnosis Discovery based on Symptom Matching.pdf

constructor-igor commented 7 years ago

The strong point of our solution when compared to the aforementioned solutions is the possibility to reduce errors caused by different probabilistic relationships between findings and diagnoses in different patient populations. The reduction is done by utilizing a data set with registered disease cases in a subpopulation.

constructor-igor commented 7 years ago

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The obtained sample has approximately 9,500 records about diagnoses and 1,700 records about corresponding symptoms. Besides symptoms, our database contains information about disease risk factors, causes of diseases, treatments and medical specialties with approximately 900, 600, 1550 and 70 records, respectively.

constructor-igor commented 7 years ago

References [1] R.W. White, and E. Horvitz, “Cyberchondria: Studies of the escalation of medical concerns in Web search,” ACM Transactions on Information Systems, vol. 27, no. 4, pp. 23:1–23:37, 2009. [2] Strategija razvoja informacionog društva u Republici Srbiji do 2020. godine [The Strategy for the Development of Information Society in the Republic of Serbia until the Year 2020], (in Serbian), Službeni glasnik Republike Srbije, vol. 51, 2010. [3] M.A. Musen, Y. Shahar, and E.H. Shortliffe, Biomedical Informatics, New York: Springer, pp. 698-736, 1995. [4] “WebMD Symptom Checker,” http://symptoms.webmd.com/ [Feb. 17, 2013]. [5] “Isabel Symptom Checker,” http://symptomchecker.isabelhealthcare.com/ [Feb. 17, 2013]. [6] R.A. Miller, H.E. Pople, Jr., and J.D. Myers, “INTERNIST-1: An Experimental Computer-Based Diagnostic Consultant for General Internal Medicine,” New England Journal of Medicine, vol. 307, pp. 427 –433, 1982. [7] G.O. Barnett, K.T. Famiglietti, R.J. Kim, E.P. Hoffer, and M.J. Feldman, “DXplain on the Internet,” in proceedings of the AMIA Annual Fall Symposium 1998, pp.607-611. [8] “Freebase,” http://www.freebase.com/ [Feb. 17, 2013]. [9] “JavaScript Object Notation,” http://www.json.org/ [Feb. 17, 2013]. [10] V. Ivančević, M. Knežević, M. Simić, I. Luković, and D. Mandić, „Dr Warehouse – An Intelligent Software System for Epidemiological Monitoring, Prediction, and Research,“ in Proceedings of DBKDA 2013, pp. 204-210. [11] S.L. Ayers, and J.J. Kronenfeld, “Chronic illness and health-seeking information on the Internet,“ Health, vol. 11, no. 3, pp. 327-347, 2007.

constructor-igor commented 7 years ago

naïve Bayes classifiers are used to estimate