IMIA Dynamic Accreditation Procedure: Suggestions, Simplicity and Efficiency.

The International Medical Informatics Association (IMIA) is the world body for biomedical and health informatics (BMHI). IMIA accreditation program allows the health and medical informatics programs around the world to reach to an international level. Staffs (professors, students, education programmes directors, others) that work on the accredited BMHI programs will have the opportunity to be engaged with organizations that possess a world-class research and education profile from other countries, which will have great impacts on their field at their institutions, within their country providing the high quality overall health services.

Toward More Successful Biomedical Informatics Education Programs and Ecosystems in the Arab World.

Biomedical & Health Informatics (BMHI) is relatively new in Arab States. However, several programs/ tracks are running, with high promises of expansion. Programs are evaluated by national authorities, not by a specialized body/association.

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients.

Objective: The main purpose of this research is the novel use of artificial metaplasticity on multilayer perceptron (AMMLP) as a data mining tool for prediction the outcome of patients with acquired brain injury (ABI) after cognitive rehabilitation. The final goal aims at increasing knowledge in the field of rehabilitation theory based on cognitive affectation.

Methods And Materials: The data set used in this study contains records belonging to 123 ABI patients with moderate to severe cognitive affectation (according to Glasgow Coma Scale) that underwent rehabilitation at Institut Guttmann Neurorehabilitation Hospital (IG) using the tele-rehabilitation platform PREVIRNEC(©).

Artificial metaplasticity neural network applied to credit scoring.

The assessment of the risk of default on credit is important for financial institutions. Different Artificial Neural Networks (ANN) have been suggested to tackle the credit scoring problem, however, the obtained error rates are often high. In the search for the best ANN algorithm for credit scoring, this paper contributes with the application of an ANN Training Algorithm inspired by the neurons' biological property of metaplasticity.