=Paper=
{{Paper
|id=Vol-1087/shortpaper4
|storemode=property
|title=A Logical Database for Geriatric Purposes
|pdfUrl=https://ceur-ws.org/Vol-1087/shortpaper4.pdf
|volume=Vol-1087
|dblpUrl=https://dblp.org/rec/conf/amw/ItaPP13
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==A Logical Database for Geriatric Purposes==
https://ceur-ws.org/Vol-1087/shortpaper4.pdf
A Logical Database for Geriatric Purposes
Guillermo De Ita Luna, Juan Carlos Pérez Vallejo, Josué Pérez Lucero
Faculty of Computer Sciences, Universidad Autónoma de Puebla
deita@cs.buap.mx, juanc.perez@cs.buap.mx
Abstract. We have developed a logical database implemented in Prolog
language as auxiliary in the diagnosis of causes and consequences of aging
processes. We have designed some belief networks to relate diseases and
its consequences, aging processes and prevention processes into a Logical
database system oriented to general purposes.
Keywords: Model-based Diagnosis, Automatic Diagnosis, Logical DataBases,
Constraint Rules.
1. Introduction
Automated reasoning and model-based diagnosis communities have spawned a
lot of work on the implementation and improvement in automatic diagnosis
and related tasks [2]. Different logical formalisms have been applied to help in
the automatic diagnosis, such as: default logic (presented in Reiter’s own HS-
algorithm, firstly), abduction or cicumscription (presented by McCarthy), as well
as network beliefs used currently in automatic diagnosis.
There are several GDE systems that were developed as a medium to inform
about specific illness. For example, Family Doctor System that works as a symp-
tom checker flowcharts allowing to easily track your symptoms and come to a
possible diagnosis [1]. Other example is, Geriatric syndrome which is a document
that contains a crosstab with geriatric information [3]. Also the Aging Systems
and Geriatrics [ASG] study reviews applications on studies of age-related con-
ditions and diseases [6].
In some countries, the people are living longer and healthier lives. Even so,
many old adults develop one or more related medical problems called geriatric
syndromes. Geriatric syndromes usually have more than one cause and involve
many parts of the body. Often, one geriatric syndrome can contribute to another,
making medical care for old people more complicated.
2. Main Diseases in the Elderly in México
Several international agencies and other demographic centres routinely prepare
national mortality estimates or life table compilations as part of their focus on
sectoral monitoring. In México, the Inegi and the Conapo are the main institu-
tions that mantain statistic on Mexican’s population and life tables. In Mexico
in the year 2005, it was informed that there were 8.4 million individuals aged
60 years and over (8.1% of the total population), and it has been projected that
there will be 17.5 million (12.4%) by 2025 and 35.7 million (24.3%) by 2050 [2].
In figure 1 is shown the main diseases causing death in México in 2010, and
for each one of those diseases what is the average affecting only to old people.
Fig. 1. Number of deaths; for general population and for old adults
In order to design a system for geriatric purposes, we are building a database
containing information about causes and consequences of the aging processes. We
have considered five aging processes, which are: Oxidation by free Radicals, Silent
Inflamation, Glycosylation, Descent of hormonal levels and Mitochondrial Dete-
rioration. In a first stage of our system, we have designed an Entity-relationship
model relating illnesses which are known to be associated with each one of the
aging processes. Currently, those relational models are being refined as belief
networks.
3. The Logical Model of our Geriatric System
Bayesian networks with their associated methods are especially suited for cap-
turing and reasoning with uncertainty. They have been around in biomedicine
and health-care for more than a decade now and have become increasingly pop-
ular for handling the uncertain knowledge involved in establishing diagnoses of
disease, in selecting optimal treatment alternatives, and predicting treatment
outcome in various different areas [2].
In our system, we have expressed the set of relations that will be expressed
as logical rules in Prolog. The system contains all logical relationships between
objects to subsequently determine the functions of conditional probabilities.As
the goal is to build a series of facts and rules written as prolog rules, the belief
network allow us to represent in a graphic way such logical rules. We are refining
the belief networks at different levels among aging processes, common diseases
in the elderly, causes, effects and methods of preventions for such diseases.
Fig. 2. A first Belief Network
4. Conclusion
Given that people older than 60 years-old show a high vulnerability, it is impor-
tant to consider the services for this sector. The system that we are developing
can be used as a support to increase a culture in the prevention of degenerative
diseases affecting to that population, because knowing which are the factors of
risk, allow them to correct their lifestyle.
We have designed some belief networks to relate degenerative diseases and its
consequences, aging processes and aged care processes into a Logical database
system oriented to general purposes. Such Database is written in Prolog languaje.
References
1. FamilyDoctor.org. http://familydoctor.org/familydoctor/es/diseases-
conditions/diabetes.printerview.all.html.
2. Andreas Bauer, Simplifying diagnosis using LSAT: a propositional approach to rea-
soning from first principles, Lecture Notes in Computer Science Volume 3524, (2005),
pp 49-63
3. Medline Plus: http://vsearch.nlm.nih.gov/vivisimo/cgi-bin/query-
metav%3Aproject=medlineplus-spanish&query=diabetes.
4. Lopez A., Salomon J., Ahmad O., Murray C., Mafat D., Life tables for 191 countries:
Data, Methods and Results, GPE Disc. Paper Series No.9, EIP/GPE/EBD, World
Health Organization
5. Suárez., M. V. (s.f.). SANOFI http://www.siempreatulado.com.mx/satlweb/servlet/
CtrlVerArt?clvart=14237&titulo=Embolia%20Cerebral
%20la%20obstrucci%C3%B3n%20que%20debes%20evitar%20a%20toda%20costa.
6. Center for Scientific Review, http://public.csr.nih.gov/StudySections/
IntegratedReviewGroups/BDCNIRG/ASG/Pages/default.aspx