Researchers in India have developed an improved expert system for the diagnosis of thyroid disease. They describe details of their approach to screening medical data in a forthcoming issue of the International Journal of Computational Science and Engineering.
Jaganathan Palanichamy and Rajkumar Nallamuthu of the PSNA College of Engineering and Technology, in Tamilnadu, India, have descried that thyroid can effectively be diagnosed through proper and careful interpretation of the thyroid data but the classification of a raw dataset from patient records can also allow undiagnosed thyroid problems to be discovered through computerized screening.
An overactive thyroid can lead to increased perspiration, a raise pulse, tremors, anxiety, nervousness, and irritability, insomnia, thinning of the skin, fine brittle hair, and muscular weakness. Sluggish thyroid in contrast might cause constipation, cold intolerance, decreased sweating, a slow pulse, depression, dry skin and poor female fertility. Thyroid disease is often asymptomatic and is commonly undiagnosed. It is obviously less of a clinical problem if there are no symptoms but left untreated symptoms can ultimately become apparent causing various problems for patients with either an overactive or a sluggish thyroid.
They claim a accuracy of 93 % in diagnosing thyroid disease.
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Journal Reference:
- Jaganathan Palanichamy and Rajkumar Nallamuthu. An expert system for optimizing thyroid disease diagnosis. Int. J. Computational Science and Engineering, 2012, 7, 232-238
