Читать книгу Advanced Healthcare Systems - Группа авторов - Страница 44

Over the years, many researchers worldwide worked in machine learning, deep learning, artificial intelligence, predictive analytics, and data science in health-related illness about future challenges and opportunities. Although some research works have been done to determine these possible causes, effects, and solutions, yet it is still a global problem. This chapter will study of thyroid disease using machine learning. Various researchers has studied research work basis for our research and understanding. There are some research papers in this regard are described below.

Parry and Kripke [11] have discussed thyroid effect on women mood disorders. Women have a higher risk of premenstrual, peripartum, and perimenopause that may occur in puberty with oral contraceptive onset and depressive illness. This paper study case reports of various persons and suggest some treatment guidelines such as Treatment-Resistant Unipolar Depression and Rapid Cycling Mood disorders. The conclusion of this paper is that, as compared to men, women have high number of depression.

Razia et al. [20] have studied various machine learning algorithms and comparison between them to achieve better accuracy in the prediction of thyroid disease. The conclusion of this paper is that the decision trees has better accuracy as compared to the naïve Bayes, SVM, and, multi-linear regression.

Pakdel and Ghazavi [12] have described selenium effect on Thyroid disorders. This paper conducts literature survey over the past 20 years’ (1995–2014) papers and discussed that this topic has increased in recent years. This literature paper was restricted to two index such as Social Science Citation Index and Science Citation Index Expanded and performing searching using keyword. The conclusion of this research is that similar studies have to be carried within next 5 years.

Priyanka et al. [1] have studied thyroid disease among women from rural and urban populations in Bangalore. It is described in this letter that every eight women in Bangalore are suffering from thyroid disease. This study was done at the actual hospital in Bangalore.

Godara [17] have predicted thyroid disease using machine learning technique. The method used to detect thyroid disease such as support vector machine and logistic regression on basis of recall, F-measure, error, ROC, and precision. To compare these techniques, Weka version is used.

Mathew [16] have studied thyroid cancer in South India. This study based on population taken from the Registry Program of National Cancer from 2005 to 2014. This paper studies the thyroid cancer patient in Thiruvananthapuram district and compares it with the other four regions Delhi, Mumbai, Bangalore, and Chennai. This paper found that Thiruvananthapuram has a higher rate of thyroid cancer in patients than in the other four regions.