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.


METHODS
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. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems.


RESULTS
Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach.


CONCLUSIONS
The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.
Tsakonas
Athanasios
A
Department of Financial and Management Engineering, University of the Aegean, 31 Fostini St., 82100 Chios, Greece. tsakonas@stt.aegean.gr
Dounias
Georgios
G
Jantzen
Jan
J
Axer
Hubertus
H
Bjerregaard
Beth
B
von Keyserlingk
Diedrich Graf
DG
D001037:Aphasia / Q000175:diagnosis; D001185:Artificial Intelligence; D003663:Decision Trees; D005260:Female; D017143:Fuzzy Logic; D005823:Genetics; D006801:Humans; D065006:Papanicolaou Test; D015203:Reproducibility of Results; D012984:Software; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis; D014626:Vaginal Smears