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Dental decision support and training system for attachment selection in removable partial denture design

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TitleInfo
Title
Dental decision support and training system for attachment selection in removable partial denture design
Name (type = personal)
NamePart (type = family)
Alturki
NamePart (type = given)
Wesam
NamePart (type = date)
1975-
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Wesam Alturki
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Srinivasan
NamePart (type = given)
Shankar
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Shankar Srinivasan
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Advisory Committee
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chair
Name (type = personal)
NamePart (type = family)
EL-Hammali
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Hind
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Hind EL-Hammali
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
DiPede
NamePart (type = given)
Louis
DisplayForm
Louis DiPede
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Health Professions
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2019
DateOther (type = degree); (qualifier = exact)
2019-01
CopyrightDate (encoding = w3cdtf)
2019
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Background: Attachment selection in removable partial dentures (RPD) design is considered one of the most challenging treatment modalities in dentistry. Any error that occur during attachment selection due to lack of proper knowledge, overwhelming number of attachments, mistreatment, multiple adjustments and repairs could result in adverse clinical consequences, and significant inconvenience to the patient as well as financial implication to both patient and provider. Attachment selection is indeed very challenging for several reasons. Firstly, the topic itself has not been widely researched and published in dental literature, and therefore the best attachment selection still remains an area prone to high error rates in decision-making. Secondly, the complexity of the topic and lack of proper knowledge that requires sound knowledge of attachment principle, which spans multiple dental displaces of endodontic, orthodontics, periodontics and prosthodontics. Furthermore, now there are an over whelming number of attachments available in the market due to high patient demand for cosmetic and aesthetic dental enhancements. It is therefore extremely difficult for dental practitioners to readily recall an extensive list of factors that determine an appropriate attachment for RPD design. This is more as for dental education students, especially for students, residents, and less experienced clinician who may not possess the adequate education, training and competencies. Although clinical experts in the area of RPD design and attachment experience and skills may be able to assist with knowledge and years of experience they may not always be around or readily available. To address this problem and gab in the education and training of dental students, residents and practitioners seeking continuing education, we have developed a clinical support and training system for RPD attachment design and implementation based on dental experts’ knowledge and literature evidence-based clinical and practice guidelines.
Methodology: The RPD attachment clinical decision support system was developed using Exsys Corvid Core software. The knowledge based of the system was setup using dental experts’ and literature evidence-based practice guidelines. In all the knowledge base was successfully loaded with more than 100 rules representing many different clinical scenarios for variable types of attachment selection in RPD. For any new input attachment case, based on the information entered by the user, the system comes up with an appropriate evidence-based recommendation and treatment plan. To ensure that the clinical decision support and training system was indeed fully capable of training and educating dental students and residents it was validated by nine expert prosthodontics using a survey style questionnaire on the various aspects of the setup and functionality of the system. The questionnaire results were statistically evaluated using Cronbach’s Alpha Coefficient Test.
Results: The Cronbach’s Alpha reliability coefficient was 0.893, which represent a good internal consistency and indicates an overall agreement among the prosthodontic experts as to the need and viability of the system for training dental students and residents in the area of RPD attachment design. Likewise, the results of the validation questionnaire showed that all prosthodontics agreed that the system contained all of the most relevant factors for attachment selection in RPD design ensuring its utility for training and education in a real-world practice.
Conclusion: The clinical decision support and training system for RPD attachment design was successfully developed using Exsys Corvid Core software. Expert prosthodontists concurred that the system can be effectively employed for training dental student, inexperienced dentists and residents to select an appropriate attachment for RPD. It can be used to complement traditional teaching methods even in the absence of patients as part of a dental degree curriculum.
Subject (authority = RUETD)
Topic
Biomedical Informatics
Subject (authority = ETD-LCSH)
Topic
Partial dentures, Removable
Subject (authority = ETD-LCSH)
Topic
Denture attachments
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_9476
PhysicalDescription
Form (authority = gmd)
electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
1 online resource (186 pages : illustrations)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Wesam Alturki
RelatedItem (type = host)
TitleInfo
Title
School of Health Professions ETD Collection
Identifier (type = local)
rucore10007400001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/t3-nc7s-w147
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Alturki
GivenName
Wesam
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-01-11 14:09:05
AssociatedEntity
Name
Wesam Alturki
Role
Copyright holder
Affiliation
Rutgers University. School of Health Professions
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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windows xp
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2019-01-11T19:00:02
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2019-01-11T19:00:02
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