Description
| Title | SemanticCT: A Semantically-Enabled System for Clinical Trials |
| Abstract | In this talk, we propose an approach of semantically enabled systems for clinical trials. The goals are not only to achieve the interoperability by semantic integration of heterogeneous data in clinical trials, but also to facilitate automatic reasoning and data processing services for decision support systems in various settings of clinical trials. We have implemented the proposed approach in a system called SemanticCT. SemanticCT is built on the top of LarKC (Large Knowledge Collider), a platform for scalable semantic data processing. SemanticCT has been integrated with large-scale trial data and patient data, and provided various automatic services for clinical trials, which include automatic patient recruitment service (i.e., identifying eligible patients for a trial) and trial finding service (i.e., finding suitable trials for a patient). |
Other presentations by Zhisheng Huang
| Date | Title |
|---|---|
| 13 November 2006 | |
| 07 January 2008 | |
| 24 November 2008 | Ontology Versioning and Effect Space |
| 05 October 2009 | Evaluation and Benchmarking of Ontology Reasoners |
| 03 October 2011 | A Hybrid Spatial Logic for Geodetic Reasoning |
| 21 January 2013 | SemanticCT: A Semantically-Enabled System for Clinical Trials |
| 18 November 2013 | Knowledge-based Patient Data Generation |
| 01 September 2014 | Feasibility Estimation for Clinical Trials |
| 30 March 2015 | Identifying Evidence Quality for Updating Evidence-based Medical Guidelines |
| 07 March 2016 | Semantic Processing of Medical Text with NLP tools |
| 19 December 2016 | Smart Ward |
| 22 May 2017 | Constructing Disease-centric Knowledge Graphs: a case study for depression |
| 17 September 2018 | Semantic Technology for Research Data Search |