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Decision Tree Analysis and Genetic Algorithm Methods Application in Healthcare

In data mining, the decision tree analysis is used to determine the best choice from various viable options. Through this process, researchers and managers get an opportunity to evaluate the risks, benefits and inconsistencies associated with the decisions. The first step is structuring the problems or issues being faced by the organization as a tree. At the end of each branch, all the benefits are listed to help in evaluating the path with the most benefits. After the benefits have been determined, the next step involves assigning subjective probabilities to all the activities on the tree (Qu, Adam, Yasui, Ward, & Cazares, 2002). On each of the choices, the possibilities on risks, errors and ambiguities are listed to help in evaluating the best option.

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The benefits of making certain decisions are associated with consequences to develop better comparison strategies that would come up with the best decision. This enhances the decision-making process and enables corporations to develop a model for dealing with the company (Qu, Adam, Yasui, Ward, & Cazares, 2002). The company focuses on the strategies that are in place and the efficiency of the strategies selected. The persons engaged in the process find better means of engaging in the process and develop comparisons based on the models present.

Arts could be used to determine the best way to treat an individual suffering from a chronic illness. Through the strategies used, the illnesses can be determined and a solution about the patients being treated, found. A more cost-effective and efficient approach, in which the detained get their correction more economically, has been found. Here detained persons get a more practical feeling, and this helps them appreciate their correction method. The medical facilities might be used to make decisions based on various detainees and these decisions might be altered by personal reflections. These decisions may reflect the actual situation hence proving the practitioner more alternatives concerning an individual situation. The facilities holding these detainees are important in devising means of generating income, with the detainees being the resources before the training. This helps in the running of the treatment facility and at the same time adding value to the patients. The strategy is widely used and those who would want a change in the penal system of punishment advocate for it to improve the quality of the treatments (Qu, Adam, Yasui, Ward, & Cazares, 2002). The data mining process entails extraction, storage and management, analysis and presentation. This is as presented in figure 1 below.

Data Scanning

Genetic Algorithm

The other method is the genetic algorithm. In this process, the social and medical principles are tested to ascertain the correct format and approach to be used. The issues of natural and genetic selections determine the best spices to be analyzed and evaluated. Societies have frameworks put in place to critically analyze the genetic institutions in the different parts of the world (Cavill, Keun, Holmes, LIndon, & Nicholson, 2009). Genetics is used to solve problems. In addition, it is used to challenge puzzles and the basics for competent machine learning. When using the genetic algorithm technique, medical practitioners can determine the actual age and genetic structure of various individuals. Sociological perspectives view social institutions as complex organizations, especially concerning treatment. If assembled well, social and historical forces shape patients’ attributes and ensure that integration and accountability are not compromised.

This represents a situation where the patients are given priority. Their genetic characteristics are compared to other methods of data collection. Under this strategy, most individuals can be tested and related to certain illnesses, most of which are genetically motivated (Cavill, Keun, Holmes, LIndon, & Nicholson, 2009). This also assists in the development of curative alternatives, in metabolism and other biological processes. Genetics also helps in the analysis and formulation of treatment criteria.

In conclusion, the data mining process is essential in all research fields. Proper use of data mining tools increases the credibility of the information retrieved by reducing error margins and increasing precision. In medical practices and research, the above data mining tools can be applied in making treatment options and in the development of reliable and effective drugs for patients. Genetic algorithm and decision tree analysis help in ensuring that medical practices are performed to perfection.

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References

Cavill, R., Keun, H. C., Holmes, E., LIndon, J. C., & Nicholson, J. K. (2009). Genetic Algorithms for Simultaneous Variable and Sample Selection in Metabonomics. Bioinformatics, 25(1), 112-118.

Qu, Y., Adam, B. L., Yasui, Y., Ward, M., & Cazares, L. H. (2002). Boosted Decision Tree Analysis of Surface-Enhanced Laser Desorption/Ionization Mass Spectral Serum Profiles Discriminates Prostate Cancer from Noncancer Patients. Clinical Chemistry, 48, 1835-1843.

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