Oshani Seneviratne
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    • Enhancing Web Spam Detection through a Blockchain-Enabled Crowdsourcing Mechanism
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    • LLM-Based Code Generation for Querying Temporal Tabular Financial Data
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    • Transforming Personal Health AI: Integrating Knowledge and Causal Graphs with Large Language Models
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    • Explanation Ontology: A General-Purpose, Semantic Representation for Supporting User-Centered Explanations
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    • Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes
    • Linking the World's Information: Essays on Tim Berners-Lee’s Invention of the World Wide Web
    • LLM-augmented Preference Learning from Natural Language
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    • Blockchain for Social Good: Combating Misinformation on the Web with AI and Blockchain
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    • Collaboratively Learning Optimal Patient Outcomes Using Smart Contracts in Limited Data Settings
    • Data-driven Analysis of Remote Work in China during the COVID-19 Pandemic
    • Development of AI-Enabled Apps by Patients and Domain Experts Using the Punya Platform: A Case Study for Diabetes
    • Explainable Clinical Decision Support: Towards Patient-Facing Explanations for Education and Long-Term Behavior Change
    • Health Data Management for Internet of Medical Things
    • Incentivized Research Data Sharing, Reusing and Repurposing with Blockchain Technologies
    • Managing Collaborative Tasks within Heterogeneous Robotic Swarms using Swarm Contracts
    • Semantic Technologies for Clinically Relevant Personal Health Applications
    • Significant Digits: Using Large-Scale Blockchain Data to Predict Fraudulent Addresses
    • Simplifying Complex Healthcare Needs With Blockchain and Internet of Medical Things
    • BlockIoT: Blockchain-based Health Data Integration using IoT Devices
    • Applying personal knowledge graphs to health
    • Blockchain-Based Mechanism for Robotic Cooperation Through Incentives: Prototype Application in Warehouse Automation
    • BlockIoT-RETEL: Blockchain and IoT Based Read-Execute-Transact-Erase-Loop Environment for Integrating Personal Health Data
    • Data Provenance and Accountability on the Web
    • Designing for AI Explainability in Clinical Context
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    • Healthy Food Recommendation and Explanation Generation using a Semantically-Enabled Framework
    • Identifying Ingredient Substitutions Using a Knowledge Graph of Food
    • Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
    • Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
    • Mobile App Development for the Semantic Web of Things with Punya
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    • Provenance in Data Science
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    • Towards a Framework for Data Excellence in Data-Centric AI: Lessons from the Semantic Web
    • A Descriptive Analysis of US Initial Coin Offerings
    • A Survey on Personal Health Knowledge Graphs
    • A Two-Step Framework for Parkinson’s Disease Classification: Using Multiple One-Way ANOVA on Speech Features and Decision Trees
    • Applying Learning and Semantics for Personalized Food Recommendations?
    • Directions for Explainable Knowledge-Enabled Systems
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    • Knowledge Extraction of Cohort Characteristics in Research Publications
    • Semantic Graph Analysis to Combat Cryptocurrency Misinformation on the Web
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    • Swarm Contracts: Smart Contracts in Robotic Swarms with Varying Agent Behavior
    • Reflections on Successful Research in Artificial Intelligence: An Interview with Yolanda Gil
    • Reflections on Successful Research in Artificial Intelligence: An Introduction
    • Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta
    • Visualization of provenance data
    • A Proposal for Account Recovery in Decentralized Applications
    • A Semantic Platform for Developing Data-Intensive Mobile Apps
    • Abductive Reasoning over Health Data and Clinical Guidelines
    • Automating Population Health Studies through Semantics and Statistics Semantic Statistics
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    • FoodKG Enabled Q&A Application
    • FoodKG: A Semantics-driven Knowledge Graph for Food Recommendation
    • G-Prov: Provenance management for clinical practice guidelines
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    • Making Computer Science Attractive to High School Girls with Computational Thinking Approaches: A Case Study
    • Augmenting Provenance Records with Trust in Enterprise Applications
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    • Detecting Creative Commons License Violations on Images on the World Wide Web
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    • On integration issues of site-specific apis into the web of data
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    • An Extensible Computer Vision Application for Blood Cell Recognition and Analysis
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Abductive Reasoning over Health Data and Clinical Guidelines

Jan 1, 2019·
Sabbir Rashid
,
Amar Das
,
Jamie P. McCusker
,
Oshani Seneviratne
,
Deborah McGuinness
· 0 min read
Cite
Type
Conference paper
Publication
New England Computational Health Summit (NECHS) 2019
Last updated on Jan 1, 2019
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Automating Population Health Studies through Semantics and Statistics Semantic Statistics Jan 1, 2019 →

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