Vipul Kashyap

Publications of Vipul Kashyap

• A multi-layered framework for disseminating knowledge for computer-based decision support.

  Authors: Aziz A Boxwala, Beatriz H Rocha, Saverio Maviglia, Vipul Kashyap, Seth Meltzer, Jihoon Kim, Ruslana Tsurikova, Adam Wright, Marilyn D Paterno, Amanda Fairbanks, Blackford Middleton

  Journal of the American Medical Informatics Association : JAMIA. 11/2011; 18 Suppl 1:i132-9.

  There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patientThere are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows. We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines. The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.

• The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside.

  Authors: Joanne S Luciano, Bosse Andersson, Colin Batchelor, Olivier Bodenreider, Tim Clark, Christine K Denney, Christopher Domarew, Thomas Gambet, Lee Harland, Anja Jentzsch [......] Elgar Pichler, Robert L Powers, Eric Prud'hommeaux, Matthias Samwald, Lynn Schriml, Peter J Tonellato, Patricia L Whetzel, Jun Zhao, Susie Stephens, Michel Dumontier

  Journal of biomedical semantics. 01/2011; 2 Suppl 2:S1.

  Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototypeTranslational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql.

• Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

  Authors: Adam Wright, David W Bates, Blackford Middleton, Tonya Hongsermeier, Vipul Kashyap, Sean M Thomas, Dean F Sittig

  Journal of biomedical informatics. 11/2008;

  Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly andClinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

• Semantic mashup of biomedical data.

  Authors: Kei-Hoi Cheung, Vipul Kashyap, Joanne S Luciano, Huajun Chen, Yimin Wang, Susie Stephens

  Journal of biomedical informatics. 09/2008;

• Semiotic web for translational medicine.

  Authors: Arkalgud Ramaprasad, Vipul Kashyap

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2008;

  The semiotic web for translational medicine generalizes the concept of the semantic web. We present the functions of the semiotic web as a simple ontology with three dimensions, namely: (a) the fourThe semiotic web for translational medicine generalizes the concept of the semantic web. We present the functions of the semiotic web as a simple ontology with three dimensions, namely: (a) the four steps of semiotics, (b) the two processes in semiotics, and (c) the four types of research. The resulting 32 combinations represent all its functions.

• Advancing translational research with the Semantic Web.

  Authors: Alan Ruttenberg, Tim Clark, William Bug, Matthias Samwald, Olivier Bodenreider, Helen Chen, Donald Doherty, Kerstin Forsberg, Yong Gao, Vipul Kashyap [......] Chimezie Ogbuji, Jonathan Rees, Susie Stephens, Gwendolyn T Wong, Elizabeth Wu, Davide Zaccagnini, Tonya Hongsermeier, Eric Neumann, Ivan Herman, Kei-Hoi Cheung

  BMC bioinformatics. 02/2007; 8 Suppl 3:S2.

  BACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research toBACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. RESULTS: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. CONCLUSION: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

• Creation of structured documentation templates using Natural Language Processing techniques.

  Authors: Vipul Kashyap, Alexander Turchin, Laura Morin, Frank Chang, Qi Li, Tonya Hongsermeier

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  Structured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrativeStructured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrative functions (e.g., evaluation and management coding, billing). One of the challenges in creating good quality documentation templates has been the inability to address specialized clinical disciplines and adapt to local clinical practices. A one-size-fits-all approach leads to poor adoption and inefficiencies in the documentation process. On the other hand, the cost associated with manual generation of documentation templates is significant. Consequently there is a need for at least partial automation of the template generation process. We propose an approach and methodology for the creation of structured documentation templates for diabetes using Natural Language Processing (NLP).

• On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

  Authors: Vipul Kashyap, Alfredo Morales, Tonya Hongsermeier

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engineWe present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

• Comparative evaluation of accuracy of extraction of medication information from narrative physician notes by commercial and academic natural language processing software packages.

  Authors: Alexander Turchin, Laura Morin, Luwam G Semere, Vipul Kashyap, Matvey B Palchuk, Maria Shubina, Frank Chang, Qi Li

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2006;

  Medication information is frequently only found in narrative physician notes. It is now possible to extract medication data from narrative documents using NLP technology. A number of commercial andMedication information is frequently only found in narrative physician notes. It is now possible to extract medication data from narrative documents using NLP technology. A number of commercial and academic NLP software packages can perform this function. In this paper we report the first comparative evaluation of their accuracy. Evaluation was carried out on 150 notes randomly selected from electronic medical record. NLP software results were compared to manual abstraction of medication data by two independent reviewers. Recall, precision and F-measure for identification of medication names, doses, frequencies, routes and inactive status were computed. For different data categories, recall ranged from 6.6% to 90.6%, and precision from 16.7% to 96.6%. Recall was highest for medication names and lowest for identification of inactive medications; there were no significant differences in precision between data categories. NLP software accuracy improved significantly over the last decade but further improvements are needed, particularly in analysis of complex sentences.

• A Knowledge Management platform for Translational Medicine.

  Authors: Tonya Hongsermeier, Vipul Kashyap

  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 02/2005;

• Definitions Management: A Semantics-Based Approach for Clinical Documentation in Healthcare Delivery.

  Authors: Vipul Kashyap, Alfredo Morales, Tonya Hongsermeier, Qi Li

  The Semantic Web - ISWC 2005, 4th International Semantic Web Conference, ISWC 2005, Galway, Ireland, November 6-10, 2005, Proceedings; 01/2005