Chest Breadths to Predict Individuals' Age - A Case Based View

It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%.

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.

Social representations of nursing students about hospital assistance and primary health care

Objective: To analyze how social representations of hospital and community care are structured in two groups of nursing students – 1st and 4th years. Method: Qualitative research oriented by the Theory of Social Representations. We used a questionnaire with Free Association of Words. Data were analyzed in the Software IRaMuTeQ 0.6 alpha 3. Results: We applied the method of Descending Hierarchical Classifi cation and obtained four classes. Class 4 has the largest social representation (30.41%) within the corpus. The two organizational axes are nurse and disease/patient in the central core. On the periphery are the care and help related to the nurse and the treatment and prevention associated with the disease. Conclusion: Social representations focus on disease/patient and on the role of nurses in the treatment, prevention, and care. Health promotion and the social determinants of health are absent from the social representations of students.

Knockin' on Digital Doors. Dealing with online [dis]credit in an era of digital scientific inquiry

This chapter aims at presenting and discussing credible online recruitment eliciting techniques targeting scientific purposes adjusted to the digital age. Based on several illustrations conducted by the author within the framework of both quantitative and qualitative inquiries, this chapter critically explores the digital ethos in three main challenges faced when dealing with online recruitment for scientific purposes: entering the normality of the everyday life, entering the idiosyncrasy of multicultural lives, and entering the chaos of busy lives. By the end, a toolbox for establishing and evaluating (dis)credibility within online recruitment strategies is presented. Moreover, it is argued that success of data collection at the present time in online environments seems to rely as ever on internal factors of the communication process vis-à-vis e-mail content, design and related strategies.