A computerized induction analysis of possible co-variations among different elements in human tooth enamel

In recent decades software tools in the area of artificial intelligence have rapidly developed for use in personal computers. Interactive rule induction utilizing mathematical algorithms has become a powerful tool in data analysis and in making rules and patterns explicit. Data from a Secondary Ion Mass Spectrometry (SIMS) elemental analysis of human dental enamel were used to elucidate co-variations between certain elements. A co-variation analysis was performed employing a computerized induction analysis program, as well as a neural network program. Both analyses, confirming each other, revealed co-variations between certain elements in dental enamel in addition to exclusion of data of no importance for chosen outcomes. The results are presented in hierarchic diagrams, in which the importance for every specific element is given by its position and level in the diagram (decision tree). From the results it became evident that elements such as chlorine and sodium expressed a high co-variation level. Similarly fluorine and potassium co-varied, as well as magnesium and the trace element strontium. It was demonstrated that data from an elemental analysis could be processed by an induction analysis to reveal co-variations between certain elements in tooth enamel. The biological significance of these data is not fully understood, and further analyses in the field are needed.