Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

An Artificial Intelligence Approach to Individuals' Age Assessment

A link between patterns of pelvic growth and human life history is supported by the finding that, cross-culturally, variation in maturation rates of female pelvis are correlated with variation in ages of menarche and first reproduction, i.e., it is well known that the human dimensions of the pelvic bones depend on the gender and vary with the age. Indeed, one feature in which humans appear to be unique is the prolonged growth of the pelvis after the age of sexual maturity. Both the total superoinferior length and mediolateral breadth of the pelvis continues to grow markedly after puberty, and do not reach adult proportions until the late teens years. This continuation of growth is accomplished by relatively late fusion of the separate centers of ossification that form the bones of the pelvis. Hence, in this work we will focus on the development of an intelligent decision support system to predict individual’s age based on a pelvis' dimensions criteria. Some basic image processing techniques were applied in order to extract the relevant features from pelvic X-rays, being the computational framework built on top of a Logic Programming approach to Knowledge Representation and Reasoning that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

Relationship between blood pressure and psychological features of experience and behaviour among teachers

Purpose: Relationships between psychic features and psychophysical parameters, such as blood pressure, have a high relevance in research on coping with stress. We want to investigate the correlation between blood pressure and this psychic features. Methods: We investigated 79 teachers from high schools and secondary schools in and around Leipzig, Germany. Using the systolic blood pressure as an indicator, we built three groups: hypotonics, normotonics, and hypertonics. We assessed several health psychologically dependent variables and looked for differences between these groups (Chi-Square-Test). Results: Hypotonics experienced more stress and less planning and goal behaviour. Furthermore, they more often use physical exercises in order to increase their social well-being. Hypertonics, on the other hand, were driven by fear of loss of control and show a higher sense of feeling threatened. Conclusions: We could find for each group different relationships that are highly relevant to health. This results shows how psychological features and physiological regulation mechanisms are linked.