Abstract
Computer Science has contributed to social sciences since decades ago: connecting people that build virtual communities where the interactions can be investigated, developing tools for statistically analytics, designing models that allow the analysis and simulation of the most diverse types, among many others. In this article, we describe an artificial neural network to model a theoretical framework for risk, housing, and health problematic, called DRVS (Diagnostic methodology for risk determination of urban housing for health), which uses a holistic approach for community and environmental health. The methodology also exposes digital clinic history for families and communities, developed to support the acquisition of necessary data. This software has advantages for the transference and application of the DRVS in different locations since it constitutes an expert system for the determination of local social indexes and supports the quantitative validation process for the underlying social theory. On the other hand, as many artificial intelligence techniques, it has constraints: unlike explicit logic inferences, artificial neural networks work as «black boxes», not explaining how they got the result; they have a strong dependency of the representativeness of training data and introducing new knowledge that may improve their results and performance is difficult (new data, addition or remotion of determining factors for the underlying social model, weighting factors, etc.). This article also shows some techniques and ideas on how to deal with the identified constraints.
Highlights
The concept of health has long been understood as the absence of health, and including preventions, life quality, environment, public services among others
In order to acquire and generate input data to RVS v2.1, we have developed a Community and Family Clinical History (HCFC for Spanish acronym) software, which allows increasing the available information that is necessary for the training of the artificial neural network
The Inter-American Healthy Housing Network endorsed by the Pan American Health Organization has expressed interest to test the methodology and its associated software; the first transference was done to the
Summary
The concept of health has long been understood as the absence of health, and including preventions, life quality, environment, public services among others. Health is concern of health personnel (doctors, nurses, psychologists, specialists, paramedics, etc) and involves to demographers, engineers, economists, architects, geographers, statisticians, teachers, politicians, social assistants, managers, among others. All these activities tackles health with the aims of to promote general welfare of the community. When defining and planning public politics in health, Integral Health Systems must be thought beyond hospital and diseases treatment systems. These systems must include access to essential public services, education, communities strengthening and empowering, community and environmental health, among others. [1,2,3,4]
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