February 11, 2016
3:00PM
4:00PM
EST
Registration
Fee:
Free for AMIA members and students of Academic Forum member institutions; Others: $50
Presenters:
Chen Lin, MS - Applications Development Specialist, Children's Hospital Informatics Program, Children's Hospital Boston
Chen Lin, MS will discuss this month's JAMIA Journal Club selection:
Multilayered temporal modeling for the clinical domain
Complete Citation:
Lin C, Dligach D, Miller TA, Bethard S, Savova GK.
Multilayered temporal modeling for the clinical domain. J Am Med Inform Assoc. 2015 Oct 31. pii: ocv113. doi: 10.1093/jamia/ocv113. [Epub ahead of print]
Presenter
Chen Lin is an Applications Development Specialist in the Children’s Hospital Informatics Program-Natural Language Processing (CHIP-NLP) group at Boston Children’s Hospital. Chen is actively incorporating statistical and machine learning technologies into advanced NLP tasks being investigated at CHIP-NLP. Topics include automatic feature selection, coreference resolution, disease activity classification based on clinical narratives, etc.
Chen started at Children’s Hospital in June, 2011. While earning his Master’s Degree in computer science at Brandeis University, Chen worked on several projects including the development of a novel complementary mining process that made use of unused features by a priori defined phenotypes and authored interactive phenotype-mining and visualizing software. In addition, Chen has research experience in deriving human cancer gene interaction networks based on genome-wide survival analysis.
Format
40-minute discussion between the authors and the JAMIA Student Editorial Board moderators including salient features of the published study and its potential impact on practice.
20-minute discussion of questions submitted by listeners via the webinar tools.
Interactive/Evaluations
Follow @AMIAinformatics and #JAMIAJC for Journal Club information.
Participants also receive short feedback surveys to evaluate the JAMIA JC webinar.
Managers
JAMIA Journal Club managers are JAMIA Student Editorial Board members:
Mary Regina Boland, MA, Department of Biomedical Informatics, Columbia University
Matthew K. Breitenstein, PhD, Department of Health Sciences Research, Mayo Clinic
Citation
The PubMed citation for the paper under discussion is:
Lin C, Dligach D, Miller TA, et al.
Multilayered temporal modeling for the clinical domain. J Am Med Inform Assoc. 2015 Oct 31. pii: ocv113. doi: 10.1093/jamia/ocv113. [Epub ahead of print]
The abstract is available here:
http://jamia.oxfordjournals.org/content/early/2015/10/31/jamia.ocv113
Fee Statement
Students who are not AMIA members, but whose academic institutions are members of the Academic Forum, are eligible for a complimentary JAMIA Journal Club registration. Please contact Susanne Arnold at susanne@amia.org for the discount code. In the email, please include: full name, Academic Department, and the primary Academic Forum representative of that Academic Department. Note that AMIA Student memberships are $45, which allow access to JAMIA, all JAMIA Journal Clubs, and other webinars of interest to the biomedical informatics community.
Statement of Purpose
Temporality is crucial for a deeper understanding of the course of clinical events in a patient’s electronic medical records. A large part of it is recorded in the electronic medical record’s free text. Automatic temporal relation discovery has the potential to dramatically increase the understanding of many medical phenomena such as disease progression, longitudinal effects of medications, and a patient’s clinical course.
The Lin, et al study used a multilayered temporal modeling strategy to take advantage of automatic inference, reduce the complexity of temporal reasoning, and improve accuracy, especially at the macro level. Scientists with interest in natural language processing will want to consider the clinical applications of the extraction and interpretation of temporal relations discussed in this study, including question answering, clinical outcomes prediction, and the recognition of temporal patterns and timelines.
This webinar will be of particular interest to those whose research interests include NLP.
Target Audience
The target audience for this activity is professionals and students interested in biomedical and health informatics.
Learning Objective
After this live activity, the participant should be better able to:
Weigh the clinical implications of a temporal relation discovery system applied to the electronic medical record.
Faculty
Chen Lin, MS
Applications Development Specialist
Children's Hospital Informatics Program - Natural Language Processing Group
Boston Children's Hospital
Boston, MA
Accreditation Statement
The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
Credit Designation Statement
The American Medical Informatics Association designates this live activity for a maximum of 1 AMA PRA Category 1 Credit(s). Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Criteria for Successful Completion
Completion of this live activity is demonstrated by:
Viewing the live webinar
Optional submission of questions via webinar feature; option to follow @AMIAinformatics and tweet via #JAMIAJC
Completion of the evaluation survey at https://www.surveymonkey.com/r/JJC_Feb2016 and
Verification of attendance through the participant's electronic report through the individual login at www.amia.org.
The physician participant will be able to generate a CME certificate through the AMIA automated system.
For a certificate of completion, contact Pesha@amia.org.
Commercial Support
No commercial support was received for this activity.
Disclosure Policy
As a provider accredited by the ACCME, AMIA requires that everyone who is in a position to control the content of an educational activity disclose all relevant financial relationships with any commercial interest for 12 months prior to the educational activity.
The ACCME considers relationships of the person involved in the CME activity to include financial relationships of a spouse or partner.
Faculty and planners who refuse to disclose relevant financial relationships will be disqualified from participating in the CME activity. For an individual with no relevant financial relationship(s), the participants must be informed that no conflicts of interest or financial relationship(s) exist.
AMIA uses a number of methods to resolve potential conflicts of interest, including: limiting content of the presentation to that which has been reviewed by one or more peer reviewers; ensuring that all scientific research referred to conforms to generally accepted standards of experimental design, data collection, and analysis; undertaking review of the educational activity by a content reviewer to evaluate for potential bias, balance in presentation, evidence-based content or other indicators of integrity, and absence of bias; monitoring the educational activity to evaluate for commercial bias in the presentation; and/or reviewing participant feedback to evaluate for commercial bias in the activity.
Disclosures for this Activity
These faculty, planners, and staff who are in a position to control the content of this activity disclose that they and their life partners have no relevant financial relationships with commercial interests:
Faculty: Chen Lin, MS
JAMIA Journal Club planners: Mary Regina Boland, Matthew Breitenstein
AMIA staff: Susanne Arnold, Pesha Rubinstein
JAMIA Journal Club planner Michael Chiang discloses the following:
Received Grant/Research support from the National Institutes of Health
Is an unpaid member of the Scientific Advisory Board of Clarity Medical Systems
Instructions for Claiming CME/CE Credit
CME site (MyAMIA) works best with IE 8 or above version, Chrome, Safari, and Firefox.
• Login to your AMIA account on the AMIA.org website
• Go to “My Profile”
• Click “Invoices & Transactions” tab
• Scroll down to Events section and click ‘Credits’ next to “Webinar: JAMIA Journal Club - February 2016”
• Physicians: for “Select Credit Type” click “Physician” in the drop-down menu.
• For “Select Physician Credit Type” click “Physician” (not MOC-II)
• Click Submit
• Click on the AMIA Activities tab in your account; click “download” in the row for “Webinar: JAMIA Journal Club - February 2016”; you may print out your certificate
Other attendees: if you require a certificate of participation, please contact pesha@amia.org.
Contact Info
For questions about content or CE, email pesha@amia.org.