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<!--
	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=diagnosis">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=diagnosis]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for diagnosis]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/117/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/46/AgentRX"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1046/KSAT-Knowledge-infused-Self-Attention-Transformer-Integrating-Multiple-Domain-Specific-Contexts"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/906/Solving-Hard-SAT-Instances-with-Adiabatic-Quantum-Computers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/747/Validation-of-a-Large-Rheumatoid-Arthritis-Cohort-and-Preventive-Health-Screening"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/673/Rafiki-A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/674/A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/536/Playing-to-Program-Towards-an-Intelligent-Programming-Tutor-for-RUR-PLE"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/267/Cross-layer-Analysis-for-Detecting-Wireless-Misbehaviour"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/150/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/151/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior"/>
    </rdf:Seq>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction">
  <title><![CDATA[Cost-Sensitive Information Acquisition for Prediction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction</link>
  <description><![CDATA[Machine learning systems have been increasingly used in our day-to-day
activities now. Just a few examples include handwritten character
recognition systems, product recommendation systems, face detection
features of cameras, speech recognition in hands-free devices, document
ranking by search engines, fraudulent activity detection for credit card
transactions, spam detection, and medical diagnosis. A critical
component of a machine learning system is the "information" needed to
develo...]]></description>
  <dc:date>2010-04-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/117/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior">
  <title><![CDATA[Cross-layer Analysis for Detecting Wireless Misbehavior]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/117/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior</link>
  <description><![CDATA[Intrusion Detections 
Systems(IDSs) in ad hoc networks monitor other devices for
intentional deviation from protocol, i.e., misbehavior. This process
is complicated due
to limited radio range and mobility of nodes. Unlike conventional
IDSs, it is not
possible to monitor nodes for long durations. As a result IDSs suffer from
a large number of false positives. Moreover other environmental conditions like
radio interference and congestion increase false positives,
complicating classific...]]></description>
  <dc:date>2005-10-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/46/AgentRX">
  <title><![CDATA[AgentRX]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/46/AgentRX</link>
  <description><![CDATA[During the past two attempts to demonstrate our highly distributed
majordemo system we experienced many low level problems that prevented
the demo from going smoothly.  These ranged from machines being off
the network, to agents not being in the right state, to speakers being
unplugged.  It is well known that keeping a complex distributed system
up and running is a difficult task, made even all the more difficult
if many of the components are partially or completely autonomous.
This pr...]]></description>
  <dc:date>2003-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices">
  <title><![CDATA[Exploring the Impact of Increased Health Information Accessibility in Cyberspace on Trust and Self-care Practices]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1176/Exploring-the-Impact-of-Increased-Health-Information-Accessibility-in-Cyberspace-on-Trust-and-Self-care-Practices</link>
  <description><![CDATA[More health information is in cyberspace than ever before, presenting
both opportunities and challenges for health information
seeking and self-care practices, particularly in underserved populations
who face health disparities for various reasons, including
limited healthcare access and high costs. We have investigated the
effect of increased health information accessibility in cyberspace on
self-care practices and trust in underserved populations of African
descent by surveying how i...]]></description>
  <dc:date>2024-06-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach">
  <title><![CDATA[Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1099/Developing-Ethics-and-Equity-Principles-Terms-and-Engagement-Tools-to-Advance-Health-Equity-and-Researcher-Diversity-in-AI-and-Machine-Learning-Modified-Delphi-Approach</link>
  <description><![CDATA[Background:

Artificial intelligence (AI) and machine learning (ML) technology design and development continues to be rapid, despite major limitations in its current form as a practice and discipline to address all socio-humanitarian issues and complexities. From these limitations emerges an imperative to strengthen AI/ML literacy in underserved communities and build a more diverse AI/ML design and development workforce engaged in health research.

Objective:

AI/ML has the potential to...]]></description>
  <dc:date>2023-09-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1046/KSAT-Knowledge-infused-Self-Attention-Transformer-Integrating-Multiple-Domain-Specific-Contexts">
  <title><![CDATA[KSAT: Knowledge-infused Self Attention Transformer -- Integrating Multiple Domain-Specific Contexts]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1046/KSAT-Knowledge-infused-Self-Attention-Transformer-Integrating-Multiple-Domain-Specific-Contexts</link>
  <description><![CDATA[Domain-specific language understanding requires integrating multiple pieces of relevant contextual information. For example, we see both suicide and depression-related behavior (multiple contexts) in the text ``I have a gun and feel pretty bad about my life, and it wouldn't be the worst thing if I didn't wake up tomorrow''. Domain specificity in self-attention architectures is handled by fine-tuning on excerpts from relevant domain-specific resources (datasets and external knowledge - medical...]]></description>
  <dc:date>2022-10-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/906/Solving-Hard-SAT-Instances-with-Adiabatic-Quantum-Computers">
  <title><![CDATA[Solving Hard SAT Instances with Adiabatic Quantum Computers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/906/Solving-Hard-SAT-Instances-with-Adiabatic-Quantum-Computers</link>
  <description><![CDATA[Regardless of debates between "P" and "NP", current classical computers can only approximate global optimum solutions through applying heuristics and meta-heuristics. Despite remarkable advancements that have been provided through distributing the computations over many processing units, exploring exponentially large spaces is still out of reach for indecomposable problems. Boolean satisfiability problem (SAT) plays a cornerstone role for countless complex real-world problems -ranging from mo...]]></description>
  <dc:date>2018-12-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management">
  <title><![CDATA[Clinico-genomic Data Analytics for Precision Diagnosis and Disease Management]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management</link>
  <description><![CDATA[Patient data can be present in clinical notes, lab results, genomic data sources, environmental and geospatial data sources and tissue banks to name a few. A holistic view of the patient's health can be achieved when relevant data from multiple heterogeneous sources are extracted and analyzed in a personalized manner. Moreover, comparative analysis of patients can be performed when multiple patient records are viewed across these heterogeneous data sources. To address this need, we propose cl...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/747/Validation-of-a-Large-Rheumatoid-Arthritis-Cohort-and-Preventive-Health-Screening">
  <title><![CDATA[Validation of a  Large Rheumatoid Arthritis Cohort and Preventive Health Screening]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/747/Validation-of-a-Large-Rheumatoid-Arthritis-Cohort-and-Preventive-Health-Screening</link>
  <description><![CDATA[We extracted a large cohort of rheumatoid arthritis (RA) patients, on which we plan to apply big data analytics for
earlier diagnosis of RA. To help validate this cohort, we performed an initial study to answer a health services
question regarding lipid surveillance and cardiovascular risk reduction in the RA community. Cardiovascular disease
is the leading cause of death among people with RA. This disease risk is double to that of the general population.]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/673/Rafiki-A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas">
  <title><![CDATA[Rafiki: A Semantic and Collaborative Approach to Community Health-care in Underserved Areas]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/673/Rafiki-A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas</link>
  <description><![CDATA[Community Health Workers (CHWs) act as liaisons between health-care providers and patients in underserved or un-served areas. However, the lack of information sharing and training support impedes the effectiveness of CHWs and their ability to correctly diagnose patients. In this paper, we propose and describe a system for mobile and wearable computing devices called Rafiki which assists CHWs in decision making and facilitates collaboration among them. Rafiki can infer possible diseases ...]]></description>
  <dc:date>2014-10-22</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/674/A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas">
  <title><![CDATA[A Semantic and Collaborative Approach to Community Health-care in Underserved Areas]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/674/A-Semantic-and-Collaborative-Approach-to-Community-Health-care-in-Underserved-Areas</link>
  <description><![CDATA[Community Health Workers (CHWs) act as liaisons between health-care providers and patients in underserved or un-served areas. However, the lack of information sharing and training support impedes the effectiveness of CHWs and their ability to correctly diagnose patients. In this paper, we propose and describe a system for mobile and wearable computing devices called Remedy which assists CHWs in decision making and facilitates collaboration among them. Remedy can infer possible diseases and tr...]]></description>
  <dc:date>2014-07-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/536/Playing-to-Program-Towards-an-Intelligent-Programming-Tutor-for-RUR-PLE">
  <title><![CDATA[Playing to Program: Towards an Intelligent Programming Tutor for RUR-PLE]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/536/Playing-to-Program-Towards-an-Intelligent-Programming-Tutor-for-RUR-PLE</link>
  <description><![CDATA[Intelligent tutoring systems (ITSs) provide students with a one-on-one tutor, allowing them to work at their own pace, and helping them to focus on their weaker areas. The RUR Python Learning Environment (RUR-PLE), a game-like virtual environment to help students learn to program, provides an interface for students to write their own Python code and visualize the code execution (Roberge 2005). RUR-PLE provides a fixed sequence of learning lessons for students to explore.  We are extending RUR...]]></description>
  <dc:date>2011-08-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/267/Cross-layer-Analysis-for-Detecting-Wireless-Misbehaviour">
  <title><![CDATA[Cross-layer Analysis for Detecting Wireless Misbehaviour]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/267/Cross-layer-Analysis-for-Detecting-Wireless-Misbehaviour</link>
  <description><![CDATA[Intrusion detections systems (IDSs) in ad hoc networks monitor other devices for
significant deviation from protocol -- misbehavior. This process is complicated due
to limited radio range and mobility of nodes. Unlike conventional IDSs, it is not
possible to monitor nodes for long durations. As a result IDSs suffer from 
a large number of false positives. Moreover other environmental conditions like
radio interference and congestion increase false positives, complicating classification
...]]></description>
  <dc:date>2006-01-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/150/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior">
  <title><![CDATA[Cross-layer Analysis for Detecting Wireless Misbehavior]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/150/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior</link>
  <description><![CDATA[Intrusion Detections Systems(IDSs) in ad hoc networks monitor other devices for
intentional deviation from protocol, i.e., misbehavior. This process
is complicated due
to limited radio range and mobility of nodes. Unlike conventional
IDSs, it is not
possible to monitor nodes for long durations. As a result IDSs suffer from
a large number of false positives. Moreover other environmental conditions like
radio interference and congestion increase false positives,
complicating classificat...]]></description>
  <dc:date>2005-10-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/151/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior">
  <title><![CDATA[Cross-layer Analysis for Detecting Wireless Misbehavior]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/151/Cross-layer-Analysis-for-Detecting-Wireless-Misbehavior</link>
  <description><![CDATA[Intrusion Detections Systems(IDSs) in ad hoc networks monitor other devices for
intentional deviation from protocol, i.e., misbehavior. This process
is complicated due
to limited radio range and mobility of nodes. Unlike conventional
IDSs, it is not
possible to monitor nodes for long durations. As a result IDSs suffer from
a large number of false positives. Moreover other environmental conditions like
radio interference and congestion increase false positives,
complicating classificat...]]></description>
  <dc:date>2005-10-19</dc:date>
 </item>
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