About Me
Research Interests
- Machine Learning
- Time Series Learning
- Manifold Geometry
- Brain Network
- Early Warning Algorithm in ICU
Publications
2016
Hossein Mohammadhassanzadeh; William Van Woensel; Samina Raza Abidi; Syed Sibte Raza Abidi
A Semantic Web-based Approach to Plausible Reasoning for Improving Clinical Knowledge Engineering Proceedings Article
In: IEEE International Conference on Biomedical and Health Informatics, Las Vegas, 2016.
Abstract | BibTeX | Tags: Clinical Decision Support Systems, Plausbile Reasoning, Semantic Web
@inproceedings{Mohammadhassanzadeh2016,
title = {A Semantic Web-based Approach to Plausible Reasoning for Improving Clinical Knowledge Engineering},
author = {Hossein Mohammadhassanzadeh and William Van Woensel and Samina Raza Abidi and Syed Sibte Raza Abidi},
year = {2016},
date = {2016-02-24},
urldate = {2016-02-24},
booktitle = {IEEE International Conference on Biomedical and Health Informatics, Las Vegas},
abstract = {In this paper, we present a semantic web based knowledge engineering approach to extend the coverage of medical knowledge-based systems in order to solve complex medical queries that demand the integration of deterministic and plausible knowledge. We leverage plausible reasoning mechanisms, which exploit associations between the underlying domain-specific data, as well as tentative domain knowledge, to extend the coverage of a medical knowledge base. We demonstrate that Semantic Web technologies, due to their efficient solutions for federated data management and built-in DL-based inferencing methods, offer useful opportunities to support plausible reasoning for medical decision support tasks. We evaluated our multi-strategy medical reasoning approach using real-world medical data. Our results illustrate that plausible reasoning improved the knowledge coverage of the original medical knowledge base by 10-12%, and in turn helped to solve complex disease diagnostic queries.},
keywords = {Clinical Decision Support Systems, Plausbile Reasoning, Semantic Web},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we present a semantic web based knowledge engineering approach to extend the coverage of medical knowledge-based systems in order to solve complex medical queries that demand the integration of deterministic and plausible knowledge. We leverage plausible reasoning mechanisms, which exploit associations between the underlying domain-specific data, as well as tentative domain knowledge, to extend the coverage of a medical knowledge base. We demonstrate that Semantic Web technologies, due to their efficient solutions for federated data management and built-in DL-based inferencing methods, offer useful opportunities to support plausible reasoning for medical decision support tasks. We evaluated our multi-strategy medical reasoning approach using real-world medical data. Our results illustrate that plausible reasoning improved the knowledge coverage of the original medical knowledge base by 10-12%, and in turn helped to solve complex disease diagnostic queries.