Advanced Healthcare Systems. Группа авторов
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Название: Advanced Healthcare Systems
Автор: Группа авторов
Издательство: John Wiley & Sons Limited
Жанр: Программы
isbn: 9781119769279
isbn:
3.5.4 Logistic Regression
Logistic regression is a supervised learning algorithm that is used to estimate target variables. The nature of the target or dependent variable is dichotomous, meaning that yes or no, there will be only two possible classes. In healthcare, logistic regression is used to predict a patient’s readmitted whether a patient is readmitted to a hospital or not. It can be divided into two classes: either the patient is not admitted or is not readmitted. Logistic regression can be used to classify whether a person will be prone to cancer due to environmental variables such as smoking habit, highway, and drinking alcohol [18].
3.5.5 Naïve Bayes
Naïve Bayes algorithm is used for prediction of disease. This algorithm trains label data sets and for this they must be trained on label data sets. This algorithm works on the basis of prior probability. The prior probability is the probability of disease that is based on its symptoms and is conducted on a data set.
This algorithm is used to predict the disease based on the maximum value between classes and that class will represent its disease or will be selected [19].
ML has contributed a considerable number of disciplines in recent years including healthcare, vision, and natural language processing. There are several machine learning approaches that are analyzed and used for the diagnosis of thyroid disease. The analysis shows that all the papers use different machine learning technologies and show different accuracy. In most research paper, it suggests that logistic regression and decision tree have obtained better accuracy than other algorithms, as shown in Figure 3.4.
Figure 3.4 Analysis of machine learning approach on thyroid.
3.6 Conclusion
The prevalence of thyroid disease in the Earth is still worrisome today, which is seen as a major threat to human life and leading to increased research. Thyroid and thyroid cancers occur mostly in women with a ratio of 3:1 compared to men. Various machine learning approaches have been implemented to predict or detect thyroid disease so that treatment for it is less complex and will increase the patient’s chances of recovery. There is a need to develop machine learning algorithms to analyze the effects of thyroid and thyroid cancer which require the minimum parameters of an individual to detect the thyroid and keeps both the time and money of the patient.
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