Researchers from the Faculty of Dentistry at the University of Hong Kong, the first artificial intelligence system in the world, has developed the risk of dental decay in children at a level of age separately, with a precision of more than 90 percent.
The team explained that this system paves the way for a revolution in the field of prevention and early care in oral health, and the results were published, Friday, in the “Cell Host & Microbe” patrol.
Dental decay in children is one of the most common chronic diseases in childhood globally. It is often caused by the accumulation of bacteria in the mouth due to a lot of intake of sugars and lack of good care of dental hygiene, which leads to the erosion of the enamel layer and the formation of holes. The problem usually begins in the upper front teeth, then extends to other teeth if they are not treated, and it may cause severe pain, difficulty eating and sleeping, and negatively affects the child’s growth and academic achievement.
It is interesting that early childhood bodies do not afflict all the teeth of the same degree, but rather targeting some of them, which remains a medical puzzle for a long time.
In order to understand this phenomenon, the researchers cooperated with the Chinese Academy of Sciences, to conduct an extensive study that included 2504 samples of plaque layers on the teeth of 89 children between the ages of 3 and 5 years, over a year.
The team used advanced microbial analysis techniques, which included the DNA sequence and complete metaginom analysis, to detect the fine differences in the composition of the microbes between the front and back teeth in the healthy mouth, and the extent of its association with the development of the decay. The results revealed that there is a natural microbial gradient from the front teeth to the background, affected by factors such as the flow of saliva and the composition of the teeth. At the beginning of the bars, this balance is disturbed, and the microbes begin to move between the places, which leads to early changes that can be monitored before any clinical symptoms appear.
Based on these discoveries, the researchers developed an artificial intelligence system called “Spatial-Mic”, the first of its kind that is able to analyze the microbial fingerprint of each age separately and predict the risk of bodies.
The system showed a precision of 98 percent in the detection of the existing bodies, and 93 percent in predicting its occurrence two months before its appearance, clearly surpassing the traditional methods that evaluate oral health in general.
The researchers emphasized that these results changed the prevailing medical concept about tooth decay, as it is no longer seen as an inevitable matter, but it has become possible to predict and prevent it accurately, based on the understanding of microbial changes at each age separately.
The team hopes to expand the scope of the study to include more diverse population groups, and work to develop a practical clinical test used in dental clinics around the world, as a step towards improving children’s health and early protection from bars, which provides them with a better health start in their lives.
