Staff View
Assesment of patient response to targeted cancer therapy using multi-frequency impedance cytometry and supervised machine learning

Descriptive

TitleInfo
Title
Assesment of patient response to targeted cancer therapy using multi-frequency impedance cytometry and supervised machine learning
Name (type = personal)
NamePart (type = family)
Ahuja
NamePart (type = given)
Karan Shashi
NamePart (type = date)
1995-
DisplayForm
Karan Shashi Ahuja
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Javanmard
NamePart (type = given)
Mehdi
DisplayForm
Mehdi Javanmard
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2018
DateOther (qualifier = exact); (type = degree)
2018-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2018
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
We present a novel method to rapidly assess patient response to targeted cancer therapy, where anti-neoplastic agents are conjugated to antibodies targeting surface markers on tumor cells. We have fabricated and characterized a device capable of rapidly assessing tumor cell viability in response to the drug using multi-frequency impedance spectroscopy in combination with supervised machine learning for enhanced classification accuracy. Currently commercially available devices for the analysis of cell viability are based on staining with Trypan blue. Staining fundamentally limits the subsequent characterization of these cells as well as further molecular analysis, and requires 0.5-1.0 milliliter of volume. Our approach only requires 50 microliters of volume and avoids staining allowing for further molecular analysis. To the best of our knowledge, this work presents the first comprehensive attempt in using phase change obtained from impedance cytometry data to assess viability of cells. Use of impedance cytometry to quantify cancer cells from blood cells was also explored.
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
Subject (authority = ETD-LCSH)
Topic
Microfluidics
Subject (authority = ETD-LCSH)
Topic
Cancer--Treatment
Subject (authority = ETD-LCSH)
Topic
Machine learning
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8841
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xi, 50 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Karan Shashi Ahuja
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3222Z6F
Genre (authority = ExL-Esploro)
ETD graduate
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Ahuja
GivenName
Karan
MiddleName
Shashi
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2018-04-11 14:45:15
AssociatedEntity
Name
Karan Ahuja
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
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
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
CreatingApplication
Version
1.7
ApplicationName
Microsoft® Word 2016
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2018-04-12T11:48:17
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2018-04-12T11:48:17
Back to the top
Version 8.5.5
Rutgers University Libraries - Copyright ©2024