Advanced Analytics Initiative - Awarded Projects 2018

Title
Using advanced analytics to develop a multimodal signature of concussion and post-concussive syndrome
Project Funding
IBM, Mitacs
Principal Investigator(s)
Dr. Michael Cusimano
Institution(s) and Partner(s)
St. Michael’s Hospital (University of Toronto), Ryerson University, SOSCIP
Project Description
  • Concussions are extremely common in deployment and in military and civilian activities. The diagnosis of concussion and “post-concussive syndrome” (PCS) is currently based on a patient’s report of their symptoms and a physical exam.
  • In this study, researchers will utilize a dataset collected over the last four years (which contains MRI, neuropsychological, eye-movement, imaging and free text data) to apply complex analytical methods to define more sensitive and specific tests.
  • These tools may be used in both a military and civilian setting, allowing for more personalized treatment and recovery programs, thereby lessening the burden of concussion and PCS.
Year of Award
2018
Status
Active
Title
Using machine learning to investigate sympathetic activation of the autonomic nervous system during treatment of mild traumatic brain injury, chronic pain and post-traumatic stress disorder
Project Funding
IBM, Mitacs
Principal Investigator(s)
Dr. James Green, Dr. Adrian Chan
Institution(s) and Partner(s)
Carleton University, SOSCIP
Project Description
  • The goal of the research project is to further our understanding and clinical management of Canadian Forces service members and Veterans suffering from a complex medical triad of traumatic brain injury, chronic pain, and post-traumatic stress disorder.
  • Using a Computer Assisted Rehabilitation Environment (CAREN) this research will collect and consolidate a series of non-invasive whole-body biological measurements from patients during immersive therapy sessions in the CAREN Virtual Reality facility.
  • High-performance computing and machine learning will be used to develop and deploy real-time estimators of sympathetic neural activation of the autonomic nervous system (SAANS).
  • These systems will allow clinicians to create individualized treatment plans for patients, thereby maximizing rehabilitation benefits and avoiding costly setbacks in patient treatment.
Year of Award
2018
Status
Active
Title
Safe Harbour for Military, Veteran and Family Health Research Data
Project Funding
IBM, Mitacs, True Patriot Love
Principal Investigator(s)
Dr. Patrick Martin
Institution(s) and Partner(s)
Queen's University, The Centre for Advanced Computing
Project Description
  • CIMVHR, affiliated research partners, and IBM have identified a significant and universal issue facing health researchers that applies to MVFH research and health research for the Canadian population at large.
  • Comprehensive and complete medical records for any given population are generally not available for research purposes due to access challenges and strict privacy protection practices.
  • This project proposes to explore a safe harbour environment that includes secure data extraction and linking components and adheres to the strict policies that protect the access to the source data while facilitating creation of properly de-identified linked datasets from different sources to facilitate more complete future MVFH research.
Year of Award
2018
Status
Active

Advanced Analytics Initiative - Awarded Projects 2017

Title
HERE4U Military Version
Project Funding
IBM, Mitacs
Principal Investigator(s)
Dr. Heather Stuart
Institution(s) and Partner(s)
Queen's University, The Centre for Advanced Computing, SOSCIP, IBM Global Business Services
Project Description
  • Researchers will develop the IBM HERE4U Military Version, an instant messaging smartphone application to connect military family members to a mental health counselling solution.
  • The application will be enabled by the IBM Watson cognitive platform using an advanced "Chat Bot" conversation system.
  • Watson will engage with the client to identify a presenting problem and when clinically serious, triage to a counselor for guidance and referral.
Year of Award
2017
Status
Active
Title
Using fMRI machine learning as a predictor of PTSD phenotype and treatment outcomes among treatment-seeking CAF members, veterans, and civilians
Project Funding
IBM, True Patriot Love, Mitacs
Principal Investigator(s)
Dr. Ruth Lanius, Dr. Don Richardson, Dr. Nicholas Coupland
Institution(s) and Partner(s)
Western University, University of Alberta, Lawson Health Research Institute, Homewood Research Institute, SOSCIP
Project Description
  • The study will utilize brain imaging data (fMRI) to determine if neurobiological machine learning algorithms can predict psychiatric symptomatology and treatment outcomes in CAF members, Veterans, their families, and civilians.
  • This research will benefit CAF members and Veterans through the identification and clinical application of novel avenues to personalized medicine.
  • Researchers anticipate developing a tool that can aid in the diagnosis of PTSD and its various subtypes, as well as inform treatment guidelines.
Year of Award
2017
Status
Active
Title
Defining PTSD in EMR Data to Explore Prevalence, Patient Characteristics and Primary Care Experiences of Veterans, Families of Military Service Members and the General Population
Project Funding
IBM, Mitacs
Principal Investigator(s)
Dr. Don Richardson, Dr. Alexander Singer
Institution(s) and Partner(s)
Western University, University of Manitoba, Queen’s University, The Centre for Advanced Computing, Calian
Project Description
  • Researchers will apply algorithmic and natural language processing techniques to establish a validated definition to identify PTSD within electronic medical records (EMR) and to identify key features related to suicide attempts and moral injury.
  • This research will benefit CAF members, Veterans, and their families through the identification and clinical application of predictors of moral injury, suicidal behaviours, and patterns of comorbidity.
  • The research team anticipates that the findings will provide much needed insight into the primary care experiences of patients with PTSD including a cohort of Veteran and related family members, as well as be generalizable to similar treatment-seeking military and veteran populations.
Year of Award
2017
Status
Active