Computational Methods for Data Analysis in Clinical Medicine: Issues and Rules

Ding Chao; Florenly*, Liena

Abstract: The wide availability of new computation tools to perform data analysis and analytical modeling makes medical informatics selection methodical. The professionals must consider this to ensure the most appropriate approach to address difficulties and issues of clinical prediction. Above all, the so-called “data mining” methods could offer methodological resolutions to consider the analysis of medical data and the construction of predictive models. A wide variety of these methods require up-front rules to support physicians and doctors in the most suitable selection of data mining (DM) tools, to construct and validate the predictive models, and the distribution of predictive models in clinical settings and surroundings. The scope and role of the field of research in analytical DM have been discussed in this paper, which is the main aim of this paper. Analytical DM has become a vital tool for researchers, clinicians, and physicians. With the integration of partial and clinic-related data, recently, genomic medicine has been efficiently paid attention to and grown to gain drive. Besides, this field has also gained new groups of complicated problems to be solved.

FULL TEXT PDF 1-4 ] DOI: 10.30566/ijo-bs/2021.special.03

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