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Upcoming Speaker: May 10, 2017 

Innovation Through Collaboration: New Models Emerging in Pediatrics for an Integrated Data-driven Healthcare Ecosystem

Dr. Adam Resnick

Session Details...

An invitation: If you are interested in presenting your work to our diverse audience of informaticists; basic, translational, and clinical researchers; software developers; and others interested in exploring the uses of informatics in cancer research, contact Eve Shalley at eve.shalley@nih.gov or 240-276-5194.

Welcome to the CBIIT Speaker Series Wiki 

The NCI Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics community. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin.

Speakers represent many different institutions, and the topics they address are wide-ranging. View a list of all past speakers, and view their presentations on our NCI CBIIT Speaker Series YouTube playlist!

For help accessing NCI CBIIT Speaker Series files, go to Help Downloading Files.

Location: 9609 Medical Center Drive, Rockville, Maryland 20850

Speaker Series Guidelines for Speakers: Download Word document

Questions or suggestions? If you have questions or would like to recommend a speaker, please email Eve Shalley at eve.shalley@nih.gov

Please refer to the Speaker Calendar below for upcoming speakers.

Upcoming Speakers:

May 10: Adam Resnick, Children’s Hospital of Philadelphia

May 24: Brad Erickson and Eliot Siegel

June 7: Vivek Navale, National Institutes of Health

June 21: Aviv Regev, MIT, Broad Institute

July 5: Paul Fearn, NCI Surveillance Informatics Branch

CBIIT Speakers

SYNOPSIS:

Session details...

SYNOPSIS:

BD2K Aztec is a global biomedical resource discovery index that allows users to simultaneously search a diverse array of tools. The resources indexed include web services, standalone software, publications, and large libraries composed of many interrelated functions. Aztec will ensure that software tools remain findable in the long term by issuing persistent DOIs and routinely updating metadata for the entire index. Aztec’s established ontologies and robust API support the programmatic query of its entire database, as well as the construction of indexes for specialized subdomains. Aztec is currently in its alpha-release phase (version 1.1), in which it is being evaluated and tested by internal users at UCLA, as well as invited external users at Sage Bionetworks, TSRI, and EMBL-EBI. Their feedback and comments have been documented and incorporated into Aztec's next release.

Join the conversation on Twitter, follow along with @NCI_NCIP and #CBIITSS during the presentation.


Session details...

Michael Crusoe SYNOPSIS:

This talk will introduce the Common Workflow Language (CWL) project. In July 2016 the CWL team released standards that enable the portable, interoperable, and executable description of command line data analysis tools and workflow made from those tools. These descriptions are enhanced by CWL's first class (but optional) support for Docker containers. The state of CWL adoption and examples of bioinformatic collaborations across many continents using CWL will be reviewed. Attendees who want to play with CWL prior to attending the presentation are invited to go through the "Gentle Introduction to the Common Workflow Language" tutorial on any OS X or Linux machine on their own time: http://www.commonwl.org/v1.0/UserGuide.html 

Session details...

Tina Hernandez-Boussard SYNOPSIS:

Prostate cancer is the most common malignancy in men and newly diagnosed men face complex treatment choices, each with different risks of acquired morbidities, including patient-centered outcomes (PCOs). Current government initiatives highlight the need to incorporate PCOs into healthcare quality metric evaluations and the widespread implementation of electronic health records (EHRs) provides opportunities to do so. However, efforts to assess quality metrics in EHRs have been limited because most relevant data are not reliably captured in structured formats. Instead they are buried as non-structured, free text recorded by clinicians. Leveraging the power of computational resources for processing the vast amount of medical information residing in EHRs, we achieve automation and precision in the evaluation of both process and outcome quality metrics, including metrics focused on PCOs.

To develop our approach, we first built a patient cohort using ICD-9/10 diagnosis codes to identify prostate cancer patients. Patients are confirmed in the California Cancer Registry, which returns tumor characteristics and treatment data on all patients with a confirmed cancer diagnosis, including complete historical record of disease pathology. Next we create novel ontological representations of quality metrics, many that are non-prostate specific. Each quality metric determines the target terms and concepts to extract from the EHRs. These terms may include diagnostic procedures and tests and their results, therapeutic procedures, and drugs. Terms are mapped to a standardized medical vocabulary (e.g., SNOMED or RxNorm), enabling us to represent the elements of a metric by a concept domain and its permissible values. The structured representation of the quality metric terms are used to create quality phenotypes, which are rules involving the temporal order of components of the quality metrics. Finally, we use data mining algorithms, including Natural Language Processing (NLP) technologies to parse the clinical narrative text and extract pertinent structured information. While we test our methodology in prostate cancer patients, these approaches are applicable to all cancer patients and are the basis of a learning healthcare system. This presentation will demonstrate the feasibility of using our methods to increase the usability of existing EHRs and enhance the efficiency and accuracy of quality measurement in cancer patients, including PCO measurements.

Session details...

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