• Login
    View Item 
    •   UMB Digital Archive
    • School, Graduate
    • Theses and Dissertations All Schools
    • View Item
    •   UMB Digital Archive
    • School, Graduate
    • Theses and Dissertations All Schools
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UMB Digital ArchiveCommunitiesPublication DateAuthorsTitlesSubjectsThis CollectionPublication DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    Display statistics

    The development and performance evaluation of a computer expert system for the histopathologic diagnosis of salivary gland neoplasms

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Find Full text
    Author
    Firriolo, Francis John
    Advisor
    Sauk, John J.
    Date
    1994
    Type
    dissertation
    
    Metadata
    Show full item record
    Abstract
    The design, development, implementation and testing of a prototype, interactive histopathologic expert system (called "SAGA") capable of diagnosing 15 types of primary epithelial neoplasms of salivary glands is described in this study. SAGA incorporates a multiple subprogram modular design architecture and makes use of multiple reasoning methodologies, including: data-driven and goal directed rule-based reasoning, linear pattern recognition, and Bayesian classification. The system's user interface incorporates both a "hypertext" context-sensitive information assistance facility and the video display of scanned photomicrographic histopathologic images. SAGA can report a differential diagnosis of its findings with an associated assessment of its confidence in its diagnosis. The system's diagnostic performance was evaluated in a series of tests. The results of a weighted Kappa analysis of SAGA's diagnoses versus those of four human expert oral pathologists for a set of 20 salivary gland neoplasm test cases indicate no statistical difference in diagnostic performance between the system and the human experts, and each of the experts in relation to the others in the group, as demonstrated by the use of Wilcoxon rank sums test. The results of a modified version of Turing's test of artificial intelligence demonstrated no statistically significant difference in the number of cases a judge disagreed with SAGA's diagnoses versus the number of cases they disagreed with the diagnosis of four human expert pathologists for a set of twenty salivary gland neoplasm test cases, as indicated by use of Fisher's exact test on the data obtained from three experimental trials. Furthermore, it was demonstrated that an experimental group (diagnoses aided by SAGA) of novice subjects' diagnostic performance and capabilities can be significantly augmented over those of a control group (diagnoses aided by textbooks/atlases) through the use of the histopathologic expert system. An over 300% increase in the number of correct answers obtained from subjects of the experimental group (n = 26) over those of the control group (n = 26) in the diagnosis of a set of 8 salivary gland neoplasm test cases was demonstrated to be statistically significant through the use of Student's t-test and Chi-square test.
    Description
    University of Maryland, Baltimore. Pathology. Ph.D. 1994
    Keyword
    Health Sciences, Dentistry
    Health Sciences, Pathology
    Artificial Intelligence
    Computer Science
    Diagnosis, Computer-Assisted--instrumentation
    Salivary Gland Neoplasms--diagnosis
    Salivary Gland Neoplasms--pathology
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/1566
    Collections
    Theses and Dissertations School of Medicine
    Theses and Dissertations All Schools

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Policies | Contact Us | UMB Health Sciences & Human Services Library
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.