Samina Abidi

@inproceedings{glean_2022,

title = {Explainable Decision Support using Task Network Models in Notation3: Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks},

author = {William Van Woensel and Samina Abidi and Karthik Tennankore and George Worthen and Syed Sibte Raza Abidi},

year  = {2022},

date = {2022-06-17},

urldate = {2022-06-17},

booktitle = {20th International Conference on Artificial Intelligence in Medicine (AIME 2022), June 14-17, 2022, Halifax},

publisher = {Springer},

keywords = {Clinical Decision Support Systems, Clinical guidelines, Notation3, Semantic Web reasoning, Task Network Models},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{glean-demo,

title = {Clinical Guidelines as Executable and Interactive Workflows with FHIR-Compliant Health Data Input using GLEAN},

author = {William Van Woensel and Samina Abidi and Karthik Tennankore and George Worthen and Syed Sibte Raza Abidi},

year  = {2022},

date = {2022-06-17},

urldate = {2022-06-17},

booktitle = {20th International Conference on Artificial Intelligence in Medicine (AIME 2022): Demo Track, June 14-17, Halifax, 2022},

publisher = {Springer},

keywords = {Clinical Decision Support Systems, Clinical guidelines, Notation3, Semantic Web reasoning, Task Network Models},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{OSullivan2021,

title = {Towards a framework for comparing functionalities of multimorbidity clinical decision support: A literature-based feature set and benchmark cases},

author = {D O'Sullivan and W Van Woensel and S Wilk and S W Tu and W Michalowski and S Abidi and M Carrier and R Edry and I Hochberg and S Kingwell and K Kogan and M Michalowski and H O'Sullivan and M Peleg},

year  = {2021},

date = {2021-10-30},

urldate = {2021-01-01},

booktitle = {AMIA 2021 Annual Symposium},

address = {San Diego, CA},

keywords = {Clinical Decision Support Systems, Comorbidity},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{rad2021,

title = {Using Interactive Visual Analytics to Optimize in Real-Time Blood Products Inventory at a Blood Bank},

author = {Jaber Rad and Jason Quinn and Calvino Cheng and Robert Liwski and Samina Raza Abidi and Syed Sibte Raza Abidi},

year  = {2021},

date = {2021-05-29},

urldate = {2021-05-29},

booktitle = {31st Medical Informatics Europe (MIE2021)},

keywords = {Blood Inventory Management, Clinical Decision Support Systems, Visual analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{VANWOENSEL2020-COCIG1,

title = {A CIG Integration Framework to Provide Decision Support for Comorbid Conditions using Transaction-based Semantics and Temporal Planning},

author = {William Van Woensel and Samina Abidi and Borna Jafarpour and Syed Sibte Raza Abidi},

year  = {2020},

date = {2020-08-01},

urldate = {2020-08-01},

booktitle = {International Conference on Artificial Intelligence in Medicine (AIME 2020)},

abstract = {Managing comorbid conditions, i.e., patients with multiple medical conditions, is quite challenging for Clinical Decision Support Systems (CDSS) based on computerized Clinical Practice Guidelines (CPG). In case of comorbidity, CDSS will need to recommend treatments from multiple different CPG, which may adversely interact (e.g., drug-disease interactions), or introduce inefficiencies. A-priori, static integration of computerized comorbid CPG is insufficient for clinical practice. In this paper, we present a solution for dynamic integration of CPG in response to evolving health profiles. Using Description and Transaction Logics, we define a set of CIG integration semantics for encoding integration decisions that cope with comorbidity issues at execution-time. These dynamic, transaction-based semantics are well-suited to roll back prior decisions when no longer safe or efficient; or, inversely, apply new decisions when relevant. Moreover, comorbid CIG integration should consider temporal properties of CIG tasks—at execution-time, these properties will be influenced by a range of temporal constraints. Given all temporal constraints, optimal task schedules will be calculated that will determine the feasibility of CIG integration decisions.},

keywords = {Clinical Decision Support Systems, Clinical Practice Guidelines, Comorbidities, Ontology, Semantic Web},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{davis-mie-2018,

title = {Interactive Dialogue-Based Patient Education for Juvenile Idiopathic Arthritis Using Argument Theory},

author = {Ben Rose Davis and E. Stringer and Samina Abidi and Syed Sibte Raza Abidi},

url = {https://www.ncbi.nlm.nih.gov/pubmed/29678020},

year  = {2018},

date = {2018-04-24},

booktitle = {28th European Medical Informatics Conference (MIE2018), April 24 - 26},

publisher = {IOSPress},

address = {Gothenburg, Sweden},

abstract = {Families of children with Juvenile Idiopathic Arthritis need a way to interact with Patient Education Materials (PEM) so that learning occurs at their own pace, on topics that are relevant to them. This paper proposes a novel, dialogue-based approach to address these needs. Using an extended version of Toulmin's model of argument as a theory-based classification method, we digitized paper-based PEM to render an interactive dialogue. The dialogue allows the user to explore a topic with respect to their interests and apprehensions as opposed to providing a static, generic document.},

keywords = {Clinical Decision Support Systems, Health Informatics, Patient Education, Personalized Medicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{daowd-mie-2018,

title = {A Personalized Risk Stratification Platform for Population Lifetime Healthcare},

author = {Ali Daowd and Samina Abidi and Ashraf Abusharekh and Syed Sibte Raza Abidi},

url = {https://www.ncbi.nlm.nih.gov/pubmed/29678095},

year  = {2018},

date = {2018-04-24},

booktitle = {28th European Medical Informatics Conference (MIE2018), April 24 - 26},

publisher = {IOSPress},

address = {Gothenburg, Sweden},

abstract = {Chronic diseases are the leading cause of death worldwide. It is well understood that if modifiable risk factors are targeted, most chronic diseases can be prevented. Lifetime health is an emerging health paradigm that aims to assist individuals to achieve desired health targets, and avoid harmful lifecycle choices to mitigate the risk of chronic diseases. Early risk identification is central to lifetime health. In this paper, we present a digital health-based platform (PRISM) that leverages artificial intelligence, data visualization and mobile health technologies to empower citizens to self-assess, self-monitor and self-manage their overall risk of major chronic diseases and pursue personalized chronic disease prevention programs. PRISM offers risk assessment tools for 5 chronic conditions, 2 psychiatric disorders and 8 different cancers.},

keywords = {Clinical Decision Support Systems, Health Informatics, Personalized Medicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Abidi2016b,

title = {A Digital Health System to Assist Family Physicians to Safely Prescribe NOAC Medication},

author = {Samina Raza Abidi and Jafna Cox and Ashraf Abusharekh and Nima Hashemian and Syed Sibte Raza Abidi},

doi = {10.3233/978-1-61499-678-1-519},

year  = {2016},

date = {2016-08-15},

booktitle = {Exploring Complexity in Health: An Interdisciplinary Systems Approach. 26th European Medical Informatics Conference (MIE2016), Munich},

volume = {228},

pages = {519-523},

publisher = {IOS Press},

series = {Studies in Health Technology and Informatics},

abstract = {Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Generally, the therapeutic options for managing AF include the use of anticoagulant drugs that prevent the coagulation of blood. New Oral Anticoagulants (NOACs) are not optimally prescribed to patients, despite their efficacy. In Canada, NOAC medications are not directly available to patients who belong to provincial benefits programs, rather a NOAC special authorization process establishes the eligibility of a patient to receive a NOAC and be paid by the provincial Pharmacare program. This special authorization process is tedious and paper-based which inhibits physicians to prescribe NOAC leading to suboptimal AF care to patients. In this paper, we present a computerized NOAC Authorization Decision Support System (NOAC-ADSS), accessible to physicians to help them (a) determine a patient eligibility for NOAC based on Canadian AF clinical guidelines, and (b) complete the special authorization form. We present a semantic web based system to ontologically model the NOAC eligibility criteria and execute the knowledge to determine a patient NOAC eligibility and dosage},

keywords = {Clinical Decision Support Systems, Clinical Practice Guidelines, Digital Health},

pubstate = {published},

tppubtype = {inproceedings}

}

@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}

}

@inproceedings{DBLP:conf/medinfo/JafarpourAAA15,

title = {INITIATE: An Intelligent Adaptive Alert Environment},

author = {Borna Jafarpour and Samina Raza Abidi and Ahmad Marwan Ahmad and Syed Sibte Raza Abidi},

url = {http://dx.doi.org/10.3233/978-1-61499-564-7-285},

doi = {10.3233/978-1-61499-564-7-285},

isbn = {978-1-61499-563-0},

year  = {2015},

date = {2015-08-23},

booktitle = {MEDINFO 2015: eHealth-enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics, Sao Paulo, Brazil},

pages = {285--289},

publisher = {IOS Press},

keywords = {Alert Fatigue, Clinical Decision Support Systems, Knowledge Management},

pubstate = {published},

tppubtype = {inproceedings}

}