title: Decision support systems to identify different species of malarial parasites.
abstract: In this project, medical expert systems were designed to aid technicians, students and scientists in identifying various species of malarial parasite from blood smears. The rule based system was found to intelligently ask pertinent questions to accurately and efficiently identify the species of malarial parasite. The probabilistic system provided quantitative feedback as to the likelihood of a diagnosis of a species of malaria. Medical expert systems can potentially streamline the process of malarial species identification, and can aid in training new technicians and scientists in this important skill.
authors.affiliation: School of Health Information Sciences, University of Texas - Health Science Center at Houston, USA.
authors.forename: Prabhu
authors.initials: P
authors.lastname: Shankar
authors.forename: Muhammad
authors.initials: M
authors.lastname: Walji
authors.forename: Asma
authors.initials: A
authors.lastname: Ali
authors.forename: Kathy A
authors.initials: KA
authors.lastname: Johnson-Throop
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D005103:Expert Systems; D006801:Humans; D008288:Malaria / Q000175:diagnosis / Q000469:parasitology*; D010961:Plasmodium