COMPARATIVE ANALYSIS OF THE CLASSIFICATION OF HEALTH STATUS BY ARTIFICIAL INTELLIGENCE METHODS

2021 ◽  
Vol 75 (3) ◽  
pp. 129-137
Author(s):  
G. A. Tyulepberdinova ◽  
◽  
М.Е. Mansurova ◽  
F.R. Gusmanova ◽  
А.А. Nurakhanova ◽  
...  

This article considers one of the problems that does not lose its significance for the characteristics of the state of human health. The fact that an application for working with artificial intelligence algorithms using the determinants of the international classification of the functioning of several body functions has not yet been developed indicates the importance of this project to create a digital health profile. In this article, we will study the International Classification of Functioning and artificial intelligence algorithms that allow it to be used. We will consider the work on classifying the obtained data by classes according to the determinants of the international classification of functioning using artificial intelligence algorithms, comparing forecast models and further optimization to create the most suitable classification model. The article presents the study of the main methods of data processing, statistics related to the state of human health from the database under consideration, and a set of machine learning methods, information search methods. It is planned to study the problems and algorithms of data analysis and their application to solve problems of the state of human health.

2020 ◽  
Vol 51 (4) ◽  
pp. 914-938
Author(s):  
Anna Cronin ◽  
Sharynne McLeod ◽  
Sarah Verdon

Purpose Children with a cleft palate (± cleft lip; CP±L) can have difficulties communicating and participating in daily life, yet speech-language pathologists typically focus on speech production during routine assessments. The International Classification of Functioning, Disability and Health: Children and Youth Version (ICF-CY; World Health Organization, 2007 ) provides a framework for holistic assessment. This tutorial describes holistic assessment of children with CP±L illustrated by data collected from a nonclinical sample of seven 2- to 3-year-old children, 13 parents, and 12 significant others (e.g., educators and grandparents). Method Data were collected during visits to participants' homes and early childhood education and care centers. Assessment tools applicable to domains of the ICF-CY were used to collect and analyze data. Child participants' Body Functions including speech, language, and cognitive development were assessed using screening and standardized assessments. Participants' Body Structures were assessed via oral motor examination, case history questionnaires, and observation. Participants' Activities and Participation as well as Environmental and Personal Factors were examined through case history questionnaires, interviews with significant others, parent report measures, and observations. Results Valuable insights can be gained from undertaking holistic speech-language pathology assessments with children with CP±L. Using multiple tools allowed for triangulation of data and privileging different viewpoints, to better understand the children and their contexts. Several children demonstrated speech error patterns outside of what are considered cleft speech characteristics, which underscores the importance of a broader assessment. Conclusion Speech-language pathologists can consider incorporating evaluation of all components and contextual factors of the ICF-CY when assessing and working with young children with CP±L to inform intervention and management practices.


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