Title: HIE-Supported Research: the CRISP Health Information Exchange Research Initiative Experience

Presenter: Ross D. Martin, MD, MHA, FAMIA

Webex: https://bit.ly/2VXvZ4W

LUNCH WILL BE PROVIDED

Abstract: In 2016, CRISP, the health information exchange (HIE) serving Maryland, DC, West Virginia, and the region, received regulatory approval as the Maryland state-designated HIE to support clinical research. Since that time, CRISP has established a basic capability for offering clinical researchers access to CRISP tools and services to support more than a dozen studies. The most common study type involves following a cohort of consented patients using two core services: the CRISP Encounter Notification Service (ENS) to receive real-time alerts when a patient has been admitted to, discharged from or transferred within one of more than 100 acute care hospitals, long-term care, or outpatient facilities in the region; and the CRISP query portal to review and download clinical documents (such as discharge summaries, surgical, radiology and encounter reports, laboratory reports, medication lists, care summaries, etc.) related to these encounters. Ross D. Martin, MD, MHA, FAMIA, Program Director of the CRISP Research Initiative, will present on CRISP experience and the policy, technical and process challenges in making HIE-mediated data available to researchers. He will also discuss plans for developing new capabilities to support researchers as they seek access to data sets that are not currently available.

ResearchMatch is an NIH-funded, national registry that brings together researchers and 130,000+ volunteers who are interested in learning more about research studies. Used nationally by over 6,000 researchers this novel platform has been helpful in recruiting research participants across many research areas, and has been particularly useful for research involving rare disease, surveys, and healthy volunteers.

You have free access to these tools through the CTSI-CN, and can use them for Feasibility or actual Recruitment. This training will give you the basics so you can be all set!

Register here: http://j.mp/2xQs2FY

REDCap 102: Surveys, Longitudinal Studies & Applications

To register, please click on this link: http://j.mp/2WMZzeU

What is REDCap?

·         Research Electronic Data Capture (REDCap) is a web-based system for data collection that allows users to build and manage online surveys and databases quickly and securely.

·         Data entry operators or people taking online surveys enter data in any web browser, either locally or from remote locations.

Why REDCap?

 ·         Easy and intuitive to design, develop, and use data collection forms/screens

·         Screen layouts are clear and simply to navigate

·         REDCap provides audit trails for tracking the history of data entry and revision

·         REDCap permits downloads of data to Excel, PDF, SAS, Stata, R, and SPSS

·         Free use for members of the CTSI-CN or member institutions

Title: On the Discovery of Feature Importance Distributions: An Overlooked Area

Presenter: James Huang, PhD

Webex: https://bit.ly/2GJj5SB

LUNCH WILL BE PROVIDED

Abstract: Detecting feature importance (predictive power) is a key problem in Machine Learning. Previous methods have been focusing on providing a single value as the estimation of the importance. However, the meaning of such value is not always obvious. Moreover, in reality a feature's importance may vary dramatically across the feature's values. A point estimation of the importance cannot capture such variations. We propose a new definition of feature importance, which directly measures a feature's predictive power. We also propose an approach to detect a high-resolution distribution of a feature's importance across the feature's values. The key novelty is a feature importance model that allows identifying significant change of importance between adjacent feature values, and a cost function that permits separating the importance of different features. Empirical results on real-world medical datasets (Breast Cancer, Parkinson's, and Drug Consumption) show that, the proposed work could help discover better knowledge, build better models, and make better decisions.

ResearchMatch is an NIH-funded, national registry that brings together researchers and 130,000+ volunteers who are interested in learning more about research studies. Used nationally by over 6,000 researchers this novel platform has been helpful in recruiting research participants across many research areas, and has been particularly useful for research involving rare disease, surveys, and healthy volunteers.

You have free access to these tools through the CTSI-CN, and can use them for Feasibility or actual Recruitment. This training will give you the basics so you can be all set!

Register here: http://j.mp/2xQs2FY

REDCap 102: Surveys, Longitudinal Studies & Applications

To register, please click on this link: http://j.mp/2WMZzeU

What is REDCap?

·         Research Electronic Data Capture (REDCap) is a web-based system for data collection that allows users to build and manage online surveys and databases quickly and securely.

·         Data entry operators or people taking online surveys enter data in any web browser, either locally or from remote locations.

Why REDCap?

 ·         Easy and intuitive to design, develop, and use data collection forms/screens

·         Screen layouts are clear and simply to navigate

·         REDCap provides audit trails for tracking the history of data entry and revision

·         REDCap permits downloads of data to Excel, PDF, SAS, Stata, R, and SPSS

·         Free use for members of the CTSI-CN or member institutions

Title: Butterfly Effect in Claims Data: Small Changes in Design Elements, Large Impacts on Causal Inference

Presenter: Rima Izem, PhD

Webex: https://bit.ly/2U3CjMl

LUNCH WILL BE PROVIDED

Abstract: Cohort studies using real world evidence from claims databases have been part of medical product post-market safety assessment for over a decade. In these studies, design elements are tailored to the main inference question of whether a drug exposure causes an adverse outcome. Some design elements are universal to all data sources while others are unique to claims data (e.g., the pharmacy dispensing record stockpiling algorithm). Our study investigated whether small changes in small design elements, coming for example from different interpretations of the same published information, can impact causal inference. This study used a multi-factorial design to assess impact of co-varying multiple design elements on different stages of the estimation process, from cohort identification to risk assessment. Data source and main design elements of a test case remained fixed but some elements co-varied across different study designs. Our results show that small changes in use of the Index Date and the stockpiling algorithm impact cohort size, length of follow-up and causal estimates. Standardizing definitions of these design elements will help minimize a study’s potential bias and facilitate replication of study findings.

Title: Case-Based Causality: An Application of Artificial Intelligence to Epidemiology and Public Health

Presenter: Douglas Weed, MD, MPH, PhD

Webex: https://bit.ly/2tw4iED

LUNCH WILL BE PROVIDED

Abstract: Causality in public health is a complex and controversial issue, involving epidemiological and toxicological studies and a family of methods discussed and debated for decades: the general scientific method, study design and statistical methods, and research synthesis methods such as the systematic narrative review, meta-analysis, and criteria-based methods of causation.  These have been applied to occupational, environmental, and lifestyle exposures as well as diverse outcomes such as cancer, neurological disorders, cardiovascular diseases, and psychiatric conditions.  We bring an artificial intelligence (AI) method—Case-Based Reasoning (CBR)—to bear on the issue of causality. The 5 “Rs” of Case-Based Causality (CBC) will be described and applied to current issues in epidemiology and public health.  Also, the relationship of CBC to existing methods of causal inference will be noted as well as the links between CBC and the concept of reliability.  Fundamentally, Case-Based Causality is a method for examining whether a body of evidence can be considered causal by the extent to which its characteristics are similar to bodies of evidence from known (i.e. established) causal relationships.

A Gentle Introduction to Natural Language Processing for Clinical & Translational Researchers

Clinicians, researchers and graduate students are welcome to attend this free, one-day workshop that will introduce the Natural Language Processing (NLP) approach and provide guidance on:

• How to refine your research questions most effectively for NLP approaches;

• What kind of data you need to answer those questions; and

• What NLP techniques are best for your projects.

* Lunch will be provided. * CME available. *

* Seating is limited * RSVP early *

Please register at HERE

For more detail, visit www.ctsicn.org or contact 

ResearchMatch is an NIH-funded, national registry that brings together researchers and 130,000+ volunteers who are interested in learning more about research studies. Used nationally by over 6,000 researchers this novel platform has been helpful in recruiting research participants across many research areas, and has been particularly useful for research involving rare disease, surveys, and healthy volunteers.

You have free access to these tools through the CTSI-CN, and can use them for Feasibility or actual Recruitment. This training will give you the basics so you can be all set!

Register here: http://j.mp/2xQs2FY

REDCap 102: Surveys, Longitudinal Studies & Applications

To register, please click on this link: http://j.mp/2WMZzeU

What is REDCap?

·         Research Electronic Data Capture (REDCap) is a web-based system for data collection that allows users to build and manage online surveys and databases quickly and securely.

·         Data entry operators or people taking online surveys enter data in any web browser, either locally or from remote locations.

Why REDCap?

 ·         Easy and intuitive to design, develop, and use data collection forms/screens

·         Screen layouts are clear and simply to navigate

·         REDCap provides audit trails for tracking the history of data entry and revision

·         REDCap permits downloads of data to Excel, PDF, SAS, Stata, R, and SPSS

·         Free use for members of the CTSI-CN or member institutions

Title: Mining the literature for genes associated with placenta-mediated maternal diseases

Presenter: Laritza Rodriguez, MD, PhD

Webex: https://bit.ly/2p6664I

LUNCH WILL BE PROVIDED

Abstract: Automated literature analysis could significantly speed up understanding of the role of the placenta and the impact of its development and functions on the health of the mother and the child. To facilitate automatic extraction of information about placenta-mediated disorders from the literature, we manually annotated genes and proteins, the associated diseases, and the functions and processes involved in the development and function of placenta in a collection of PubMed/MEDLINE abstracts. We developed three baseline approaches to finding sentences containing this information: one based on supervised machine learning (ML) and two based on distant supervision: 1) using automated detection of named entities and 2) using MeSH. We compare the performance of several well-known supervised ML algorithms and identify two approaches, Support Vector Machines (SVM) and Generalized Linear Models (GLM), which yield up to 98% recall precision and F1 score. We demonstrate that distant supervision approaches could be used at the expense of missing up to 15% of relevant documents.

Title: Characterization and Quantification of the Human Endogenous Retrovirus Transcriptome

Presenter: Matthew Bendall, PhD candidate

Mentors: Keith A. Crandall, PhD; Douglas F. Nixon, MD, PhD

Webex: https://bit.ly/2p6664I

Abstract: The human genome is host to thousands of Human Endogenous Retroviruses (HERVs) – proviral remnants of ancient exogenous retroviral infections –  that altogether comprise almost 8% of the human genome. Several lines of evidence suggest that HERVs may in fact play an important role in human biology. Currently, single-locus quantification of repetitive element transcription using next-generation sequencing (NGS) is a major technological challenge. Two important limitations have prevented this technique from being widely adopted. First, the precise location and structure of HERV elements in the genome is largely unknown; and second, computational algorithms for mapping sequence reads to repetitive elements have not been developed. In this dissertation, I aim to resolve these two challenges by creating a reference set of HERV elements in the human genome and developing a computational approach to accurately quantify HERV expression. I will use these tools to investigate HERV expression in neurodevelopment, psychiatry, and embryonic development.

ResearchMatch is an NIH-funded, national registry that brings together researchers and 130,000+ volunteers who are interested in learning more about research studies. Used nationally by over 6,000 researchers this novel platform has been helpful in recruiting research participants across many research areas, and has been particularly useful for research involving rare disease, surveys, and healthy volunteers.

You have free access to these tools through the CTSI-CN, and can use them for Feasibility or actual Recruitment. This training will give you the basics so you can be all set!

Register here: http://j.mp/2xQs2FY

REDCap 102: Surveys, Longitudinal Studies & Applications

To register, please click on this link: https://cri-datacap.org/surveys/?s=HyPAG5m9YT

What is REDCap?

·         Research Electronic Data Capture (REDCap) is a web-based system for data collection that allows users to build and manage online surveys and databases quickly and securely.

·         Data entry operators or people taking online surveys enter data in any web browser, either locally or from remote locations.

Why REDCap?

 ·         Easy and intuitive to design, develop, and use data collection forms/screens

·         Screen layouts are clear and simply to navigate

·         REDCap provides audit trails for tracking the history of data entry and revision

·         REDCap permits downloads of data to Excel, PDF, SAS, Stata, R, and SPSS

·         Free use for members of the CTSI-CN or member institutions

Title: Relationship between acute and chronic kidney disease using VA national data

Presenter: Richard Amdur, PhD

Webex: https://bit.ly/2p6664I

JOIN US FOR A ROUND TABLE LUNCH FROM 1 TO 2PM!

Abstract: Until recently, it was thought that patients who survived an episode of acute kidney injury (AKI) and returned to a normal kidney functioning (as measured by serum creatinine) would have little or no chronic kidney problems as a result. By examining large longitudinal patient samples, we and other VA researchers showed that this was not the case. We developed and validated prediction models to identify AKI patients at high risk for progression to chronic kidney disease (CKD) and end-stage renal failure (ESRD). We also showed that episodes of AKI raised the risk of later cardiovascular disease events (MI, stroke, death). Finally, we proposed a method for measuring variability in kidney functioning that was mathematically independent of slope of CKD progression, and that was a powerful predictor of CKD progression, even in initially healthy patients. Overall, our work and that of other VA researcher over the past 10 years has helped to inform a new understanding of the complex inter-relationship between AKI and CKD.

Title: Reconstruction of clone- and haplotype-specific cancer genomes karyotypes from tumor mixtures

Presenter: Sergey Aganezov, PhD, CBI

Webex: https://bit.ly/2xbnbOl

JOIN US FOR A ROUND TABLE LUNCH from 1 to 2pm!

Abstract: We introduce a novel method, Reconstructing Cancer Karotypes (RCK), for reconstructing one or more rearranged cancer genomes, or clones, that best explain the read alignments from a bulk tumor sample. RCK leverages specific evolutionary constraints on the somatic mutation process in cancer in order to reduce ambiguity in the deconvolution of admixed DNA sequence data into multiple haplotype-specific cancer clones. In particular, RCK relies on the infinite sites assumption that a genome rearrangement is highly unlikely to occur at the same nucleotide position more than once during somatic evolution. Earlier methods for analyzing cancer genome rearrangements (e.g.PREGO,Weaver,andReMixT) rely on weaker forms on the infinite sites assumption that do not account for the diploid nature of the human genome and the presence of multiple clones within a tumor. As a result, we show that these other methods can yield highly improbable reconstructions.

Register Today for the Georgetown ICBI 7th Annual Big Data in Biomedicine Symposium! 

Spaces are filling up fast!  Register Today!

Click Here to Register

Georgetown ICBI 7th Annual Big Data in Biomedicine Symposium: Health Data Science & Informatics

Friday October 26th 2018

Spotlight speakers:

Melissa Haendel, PhD

Neal Meropol, MD

The ICBI's 7th Annual Big Data in Biomedicine Symposium will be held on Friday, October 26, 2018 at the Georgetown University Conference Center.

This one-day event will include talks by academic, industry, and government leaders in clinical and translational sciences who will highlight technologies, applications of informatics science and tools to advance precision medicine.

Dr. Melissa Haendel, Director of Translational Data Science, Oregon Health & Science University & Dr. Neal Meropol, Vice President of Research Oncology at Flatiron Health will be this year's spotlight speakers. Planned sessions include:Rise of the Digital Citizen Real World Evidence and Clinical OutcomesNext Generation Data CommonsEducating the Next Generation of Health Data ScientistsPoster SessionSpecial Networking SessionThe Symposium is free for academic and government participants and will showcase exciting advances in the areas of health data analytics, informatics and related state-of-the-art technologies, and will bring together a dynamic community of innovators, research scientists, clinicians, program managers, educators, and students to exchange ideas and learn new methodologies. 

The event also offers an opportunity to network with colleagues during the evening reception and compete for the best poster award
*** ABSTRACT DEADLINE EXTENDED TO OCTOBER 12, 2018 *** For more information about the Symposium
CLICK HERE

Please join us for the launch of our Genomics Core in the GW Milken Institute School of Public Health! The program will include:

8:00am   - Breakfast Reception
8:30am   - Ribbon Cutting Celebration 
9:00am   - Guided Tours of the Genomics Lab
10:00am - Keynote address by Illumina: "Multi-omics approaches – utilizing NGS for DNA, expression and epigenetics studies"

A grab-and-go lunch will be provided, and ample opportunity for networking!

Please register using this link: http://connect.gwu.edu/site/Calendar?id=116354&view=RSVP

Visit our Genomics Core website: https://www.gwgenomics.org

ResearchMatch is an NIH-funded, national registry that brings together researchers and 130,000+ volunteers who are interested in learning more about research studies. Used nationally by over 6,000 researchers this novel platform has been helpful in recruiting research participants across many research areas, and has been particularly useful for research involving rare disease, surveys, and healthy volunteers.

You have free access to this tool through the CTSI-CN, and can use it for Feasibility or actual Recruitment. This training will give you the basics so you can be all set!

Register here: https://cri-datacap.org/surveys/?s=NYTL8AAPX9

REDCap 102: Surveys, Longitudinal Studies & Applications

To register, please click on this link: https://cri-datacap.org/surveys/?s=HyPAG5m9YT

What is REDCap?

·         Research Electronic Data Capture (REDCap) is a web-based system for data collection that allows users to build and manage online surveys and databases quickly and securely.

·         Data entry operators or people taking online surveys enter data in any web browser, either locally or from remote locations.

Why REDCap?

 ·         Easy and intuitive to design, develop, and use data collection forms/screens

·         Screen layouts are clear and simply to navigate

·         REDCap provides audit trails for tracking the history of data entry and revision

·         REDCap permits downloads of data to Excel, PDF, SAS, Stata, R, and SPSS

·         Free use for members of the CTSI-CN or member institutions