2018
Syed S.R. Abidi; Patrice C. Roy; Muhammad S. Shah; Jin Yu; Sanjun Yan
A data mining framework for glaucoma decision support based on optic nerve image analysis using machine learning methods Journal Article
In: Journal of Healthcare Informatics Research, vol. 2, no. 4, pp. 370-401, 2018.
Links | BibTeX | Tags: Classification, Clustering, Data Mining, Decision Support Systems, Optic Nerve
@article{Abidi2018,
title = {A data mining framework for glaucoma decision support based on optic nerve image analysis using machine learning methods},
author = {Syed S.R. Abidi and Patrice C. Roy and Muhammad S. Shah and Jin Yu and Sanjun Yan},
doi = {10.1007/s41666-018-0028-7},
year = {2018},
date = {2018-12-01},
journal = {Journal of Healthcare Informatics Research},
volume = {2},
number = {4},
pages = {370-401},
keywords = {Classification, Clustering, Data Mining, Decision Support Systems, Optic Nerve},
pubstate = {published},
tppubtype = {article}
}
2016
Nelofar Kureshi; Syed Sibte Raza Abidi; Christian Blouin
A Predictive Model for Personalized Therapeutic Interventions in Non-small Cell Lung Cancer. Journal Article
In: IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 1, pp. 424-431, 2016, ISSN: 2168-2208.
Abstract | Links | BibTeX | Tags: Cancer, Data Mining, Decision Trees, Health Data Analytics, Personalized Medicine, Prediction Model
@article{Kureshi:IeeeJBiomedHealthInform:2014,
title = {A Predictive Model for Personalized Therapeutic Interventions in Non-small Cell Lung Cancer.},
author = {Nelofar Kureshi and Syed Sibte Raza Abidi and Christian Blouin},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6974996&isnumber=7369993},
doi = {10.1109/JBHI.2014.2377517},
issn = {2168-2208},
year = {2016},
date = {2016-01-01},
journal = {IEEE Journal of Biomedical and Health Informatics},
volume = {20},
number = {1},
pages = {424-431},
abstract = {Non-small cell lung cancer (NSCLC) constitutes the most common type of lung cancer and is frequently diagnosed at advanced stages. Clinical studies have shown that molecular targeted therapies increase survival and improve quality of life in patients. Nevertheless, the realization of personalized therapies for NSCLC faces a number of challenges including the integration of clinical and genetic data and a lack of clinical decision support tools to assist physicians with patient selection. To address this problem, we used frequent pattern mining to establish the relationships of patient characteristics and tumor response in advanced NSCLC. Univariate analysis determined that smoking status, histology, EGFR mutation, and targeted drug were significantly associated with response to targeted therapy. We applied four classifiers to predict treatment outcome from EGFR-TKIs. Overall, the highest classification accuracy was 76.56% and the AUC was 0.76. The decision tree used a combination of EGFR mutations, histology, and smoking status to predict tumor response and the output was both easily understandable and in keeping with current knowledge. Our findings suggest that support vector machines and decision trees are a promising approach for clinical decision support in the patient selection for targeted therapy in advanced NSCLC},
keywords = {Cancer, Data Mining, Decision Trees, Health Data Analytics, Personalized Medicine, Prediction Model},
pubstate = {published},
tppubtype = {article}
}
2015
Sangwhan Cha; Ashraf Abusharekh; Syed Sibte Raza Abidi
Towards a 'Big' Health Data Analytics Platform Proceedings Article
In: First IEEE International Conference on Big Data Computing Service and Applications, BigDataService, Redwood City, CA, USA, pp. 233–241, IEEE Press, 2015, ISBN: 978-1-4799-8128-1.
Links | BibTeX | Tags: Big Data, Data Mining, Decision Support, Health Data Analytics
@inproceedings{DBLP:conf/bigdataservice/ChaAA15,
title = {Towards a 'Big' Health Data Analytics Platform},
author = {Sangwhan Cha and Ashraf Abusharekh and Syed Sibte Raza Abidi},
url = {http://dx.doi.org/10.1109/BigDataService.2015.13},
doi = {10.1109/BigDataService.2015.13},
isbn = {978-1-4799-8128-1},
year = {2015},
date = {2015-04-02},
booktitle = {First IEEE International Conference on Big Data Computing Service and Applications, BigDataService, Redwood City, CA, USA},
pages = {233--241},
publisher = {IEEE Press},
keywords = {Big Data, Data Mining, Decision Support, Health Data Analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
2013
Hossein Mohammadhassanzadeh; Hamid Reza Shahriari
Prediction of User’s Trustworthiness in Web-based Social Networks via Text Mining Journal Article
In: ISecure Journal, vol. 5, no. 2, pp. 171-187, 2013.
Abstract | Links | BibTeX | Tags: Data Mining, Social Network Analysis
@article{Mohammadhassanzadeh2013,
title = {Prediction of User’s Trustworthiness in Web-based Social Networks via Text Mining},
author = {Hossein Mohammadhassanzadeh and Hamid Reza Shahriari},
url = {http://isecure-journal.com/index.php/isecure/article/view/12-163/73},
year = {2013},
date = {2013-07-01},
journal = {ISecure Journal},
volume = {5},
number = {2},
pages = {171-187},
abstract = {In Social networks, users need a proper estimation of trust in others to be able to initialize reliable relationships. Some trust evaluation mechanisms have been offered, which use direct ratings to calculate or propagate trust values. However, in some web-based social networks where users only have binary relationships, there is no direct rating available. Therefore, a new method is required to infer trust values in these networks. To bridge this gap, this paper aims to propose a new method which takes advantage of user similarity to predict trust values without any need for direct ratings. In this approach, which is based on socio psychological studies, user similarity is calculated from the profile information and the texts shared by the users via text-mining techniques. Applying Ziegler ratios to our approach revealed that users are more than 50% more similar to their trusted agents than to arbitrary peers, which proves the validity of the original idea of the study about inferring trust from language similarity. In addition, comparing the real assigned ratings, gathered directly from users, with the experimental results indicated that the predicted trust values are sufficiently acceptable (with a precision of 61%). We have also studied the benefits of using context in inferring trust. In this regard, the analysis revealed that the precision of the predictions can be improved up to 72%. Besides the application of this approach in web-based social networks, the proposed technique can also be of much help in any direct rating mechanism to evaluate the correctness of trust values assigned by users, and increases the robustness of trust and reputation mechanisms against possible security threats.},
keywords = {Data Mining, Social Network Analysis},
pubstate = {published},
tppubtype = {article}
}
2010
Ali Daniyal; Samina Raza Abidi; Ashraf Abusharekh; Mei Kuan Wong; Syed Sibte Raza Abidi
A Knowledge-centric e-Research Platform for Marine Life and Oceanographic Research Proceedings Article
In: International Conference on Knowledge Management and Information Sharing, Valencia, Spain, October 25-28, 2010, pp. 363–366, 2010.
BibTeX | Tags: Data Mining, E-Science, Knowledge Management, Oceanography
@inproceedings{DBLP:conf/ic3k/DaniyalAAWA10,
title = {A Knowledge-centric e-Research Platform for Marine Life and Oceanographic Research},
author = {Ali Daniyal and Samina Raza Abidi and Ashraf Abusharekh and Mei Kuan Wong and Syed Sibte Raza Abidi},
year = {2010},
date = {2010-01-01},
booktitle = {International Conference on Knowledge Management and Information Sharing, Valencia, Spain, October 25-28, 2010},
pages = {363--366},
crossref = {DBLP:conf/ic3k/2010kmis},
keywords = {Data Mining, E-Science, Knowledge Management, Oceanography},
pubstate = {published},
tppubtype = {inproceedings}
}
2007
Syed Sibte Raza Abidi; Paul Habib Artes; Sanjan Yun; Jin Yu
Automated Interpretation of Optic Nerve Images: A Data Mining Framework for Glaucoma Diagnostic Support. Proceedings Article
In: Stud Health Technol Inform, pp. 1309-13, Netherlands, 2007, ISSN: 0926-9630.
Abstract | BibTeX | Tags: Classification, Clustering, Data Mining, Decision Support Systems, Optic Nerve
@inproceedings{Abidi:StudHealthTechnolInform:2007,
title = {Automated Interpretation of Optic Nerve Images: A Data Mining Framework for Glaucoma Diagnostic Support.},
author = {Syed Sibte Raza Abidi and Paul Habib Artes and Sanjan Yun and Jin Yu},
issn = {0926-9630},
year = {2007},
date = {2007-01-01},
booktitle = {Stud Health Technol Inform},
volume = {129},
number = {Pt 2},
pages = {1309-13},
address = {Netherlands},
abstract = {Confocal Scanning Laser Tomography (CSLT) techniques capture high-quality images of the optic disc (the retinal region where the optic nerve exits the eye) that are used in the diagnosis and monitoring of glaucoma. We present a hybrid framework, combining image processing and data mining methods, to support the interpretation of CSLT optic nerve images. Our framework features (a) Zernike moment methods to derive shape information from optic disc images; (b) classification of optic disc images, based on shape information, to distinguish between healthy and glaucomatous optic discs. We apply Multi Layer Perceptrons, Support Vector Machines and Bayesian Networks for feature sub-set selection and image classification; and (c) clustering of optic disc images, based on shape information, using Self-Organizing Maps to visualize sub-types of glaucomatous optic disc damage. Our framework offers an automated and objective analysis of optic nerve images that can potentially support both diagnosis and monitoring of glaucoma.},
keywords = {Classification, Clustering, Data Mining, Decision Support Systems, Optic Nerve},
pubstate = {published},
tppubtype = {inproceedings}
}
2006
Qingshuang Jiang; Syed Sibte Raza Abidi
From Clusters to Rules: A Hybrid Framework for Generalized Symbolic Rule Induction Proceedings Article
In: Advances in Machine Learning and Cybernetics, pp. 219-228, Springer, 2006.
BibTeX | Tags: Data Mining, Health Data Analytics
@inproceedings{jiang2006clusters,
title = {From Clusters to Rules: A Hybrid Framework for Generalized Symbolic Rule Induction},
author = {Qingshuang Jiang and Syed Sibte Raza Abidi},
year = {2006},
date = {2006-01-01},
booktitle = {Advances in Machine Learning and Cybernetics},
pages = {219-228},
publisher = {Springer},
keywords = {Data Mining, Health Data Analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
2005
Jin Yu; Syed Sibte Raza Abidi; Paul Habib Artes; Andrew R. McIntyre; Malcolm I. Heywood
Automated Optic Nerve Analysis for Diagnostic Support in Glaucoma Proceedings Article
In: 18th IEEE Symposium on Computer-Based Medical Systems (CBMS 2005), 23-24 June 2005, Dublin, Ireland, pp. 97–102, 2005.
Links | BibTeX | Tags: Classification, Clustering, Data Mining, Decision Support Systems, Glaucoma, Health Data Analytics, Optic Nerve
@inproceedings{DBLP:conf/cbms/YuAAMH05,
title = {Automated Optic Nerve Analysis for Diagnostic Support in Glaucoma},
author = {Jin Yu and Syed Sibte Raza Abidi and Paul Habib Artes and Andrew R. McIntyre and Malcolm I. Heywood},
url = {http://dx.doi.org/10.1109/CBMS.2005.36},
year = {2005},
date = {2005-01-01},
booktitle = {18th IEEE Symposium on Computer-Based Medical Systems (CBMS 2005), 23-24 June 2005, Dublin, Ireland},
pages = {97--102},
crossref = {DBLP:conf/cbms/2005},
keywords = {Classification, Clustering, Data Mining, Decision Support Systems, Glaucoma, Health Data Analytics, Optic Nerve},
pubstate = {published},
tppubtype = {inproceedings}
}
Qingshuang Jiang; Syed Sibte Raza Abidi
From Clusters to Rules: A Hybrid Framework for Generalized Symbolic Rule Induction Proceedings Article
In: Advances in Machine Learning and Cybernetics, 4th International Conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005, Revised Selected Papers, pp. 219–228, 2005.
Links | BibTeX | Tags: Data Mining, Health Data Analytics
@inproceedings{DBLP:conf/icmlc/JiangA05,
title = {From Clusters to Rules: A Hybrid Framework for Generalized Symbolic Rule Induction},
author = {Qingshuang Jiang and Syed Sibte Raza Abidi},
url = {http://dx.doi.org/10.1007/11739685_23},
year = {2005},
date = {2005-01-01},
booktitle = {Advances in Machine Learning and Cybernetics, 4th International Conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005, Revised Selected Papers},
pages = {219--228},
crossref = {DBLP:conf/icmlc/2005},
keywords = {Data Mining, Health Data Analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
2004
Andrew R. McIntyre; Malcolm I. Heywood; Paul Habib Artes; Syed Sibte Raza Abidi
Toward Glaucoma Classification with Moment Methods Proceedings Article
In: 1st Canadian Conference on Computer and Robot Vision (CRV 2004) 17-19 May 2004, London, Ontario, Canada, pp. 265–272, 2004.
Links | BibTeX | Tags: Data Mining, Glaucoma, Health Data Analytics
@inproceedings{DBLP:conf/crv/McIntyreHAA04,
title = {Toward Glaucoma Classification with Moment Methods},
author = {Andrew R. McIntyre and Malcolm I. Heywood and Paul Habib Artes and Syed Sibte Raza Abidi},
url = {http://doi.ieeecomputersociety.org/10.1109/CCCRV.2004.1301454},
year = {2004},
date = {2004-01-01},
booktitle = {1st Canadian Conference on Computer and Robot Vision (CRV 2004) 17-19 May 2004, London, Ontario, Canada},
pages = {265--272},
crossref = {DBLP:conf/crv/2004},
keywords = {Data Mining, Glaucoma, Health Data Analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
2002
Syed Sibte Raza Abidi; Kok Meng Hoe
Symbolic Exposition of Medical Data-Sets: A Data Mining Workbench to Inductively Derive Data-Defining Symbolic Rules Proceedings Article
In: 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), 4-7 June 2002, Maribor, Slovenia, pp. 123–128, 2002.
Links | BibTeX | Tags: Data Mining, Health Data Analytics
@inproceedings{DBLP:conf/cbms/AbidiH02,
title = {Symbolic Exposition of Medical Data-Sets: A Data Mining Workbench to Inductively Derive Data-Defining Symbolic Rules},
author = {Syed Sibte Raza Abidi and Kok Meng Hoe},
url = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2002.1011365},
year = {2002},
date = {2002-01-01},
booktitle = {15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), 4-7 June 2002, Maribor, Slovenia},
pages = {123--128},
crossref = {DBLP:conf/cbms/2002},
keywords = {Data Mining, Health Data Analytics},
pubstate = {published},
tppubtype = {inproceedings}
}