Drawing on artificial intelligence, this new technique has as its main objective is to provide professional diagnostic work conditions such as gingivitis or pyorrhea, automating this process so as to obtain a better approximation to the problem and a more tight.
A team of international scientists, which participates José Luis Salmeron, professor at the University Pablo de Olavide of Seville, has developed an intelligent system capable of assessing the severity of periodontal disease.
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Periodontal disease is a chronic bacterial infection that affects the gums and bone supporting the teeth. According to the Spanish Society of Periodontology and Osseointegration (SEPA), 59.8% of Spanish adults aged 35 to 44 years suffer gingivitis, while 25.4% would suffer periodontitis. Only 14.8% of the Spanish in this age group have healthy gums, says this organization. As an addition, recent research suggests that patients with periodontal disease are at increased risk of pancreatic cancer or coronary events.
"The presence or absence of signs, symptoms and risk factors make the diagnosis of this disease is a very complex task," says José Luis Salmeron. Symptoms of periodontal disease include tooth mobility, bleeding gums, continuous mild pain and inflammation of the gums and the main signs are the presence of plaque and periodontal pocket. They are joined by the risk factors that cause this disease, such as smoking, diabetes, hormonal changes, etc..
"Usually, doctors dentist is based on their knowledge, expertise and experience to design treatment. Therefore, there is great variation between the different treatments administered by professionals, "says researcher Pablo de Olavide. To assist in this task, this group of experts have designed a system based on Fuzzy Cognitive Maps (FCM, English acronym Fuzzy Cognitive Maps), a dynamic model based on fuzzy logic monolayer.
This technique evaluates the severity of the disease based on both the symptoms and risk factors. The relationships between the different signs, symptoms defined by fuzzy linguistic variables easily understood after the construction process of the FCM, which are transformed into numerical values using the Mamdani inference method. With this research, doctors dentists can automate or support at least the assessment of periodontal disease.
José Luis Salmeron Silvera is a professor at the University Pablo de Olavide and Director of the Computational Intelligence Laboratory. Computer Engineer and Economist with extensive experience in intelligent systems, the researcher is a member of numerous scientific societies with which it collaborates actively, such as the Internet Society, Association of Computing Machinery, Association of Logic Programming or International Rough Sets Society. His works have been published in international scientific journals impact. Today has collaborations with numerous Spanish and foreign groups, leading various national and international projects.
Mago, VK, Papageorgiou, EI, Salmeron, JL, Mage, A. 2012. Employing Fuzzy Cognitive Map for Periodontal Disease Assessment, FUZZ-IEEE 2012, IEEE International Conference on Fuzzy Systems, Brisbane, Australia
More information:
José Luis Salmerón
Polytechnic School
UPO
Email: salmeron@upo.es
Tel: 954349063
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