Rotaglide total knee arthroplasty: a long-term follow-up study.

Background: Mobile-bearing knee designs represent an alternative to conventional fixed-bearing implants in total knee arthroplasty. The purpose of this study was to determine the clinical results of a mobile-bearing knee implant.

Methods: From 1990 to 1998, 326 primary consecutive mobile-bearing total knee prostheses were implanted in 260 patients who had a mean age and standard deviation of 66.

Computational intelligence for the detection and classification of malignant lesions in screening mammography.

This report deals with the discussion of the findings obtained from the application of two computational intelligence methodologies for the detection of microcalcifications in screening mammography data. Genetic programming and inductive machine learning have been applied, in order to produce meaningful diagnostic rules for the medical staff. The data used in the experiments correspond to information acquired from two images of each breast of the patient, along with some associated patient information such as the age at time of study.

Breast tumor malignancy modelling using evolutionary neural logic networks.

The present work proposes a computer assisted methodology for the effective modelling of the diagnostic decision for breast tumor malignancy. The suggested approach is based on innovative hybrid computational intelligence algorithms properly applied in related cytological data contained in past medical records. The experimental data used in this study were gathered in the early 1990s in the University of Wisconsin, based in post diagnostic cytological observations performed by expert medical staff.

Evolving rule-based systems in two medical domains using genetic programming.

Objective: To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations.

Material: Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method.

Methods: Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction.