Initiative analytique avancée - Awarded Projects 2018

Titre
Using advanced analytics to develop a multimodal signature of concussion and post-concussive syndrome
Financement du projet
IBM, Mitacs
Chercheur(e)(s) principal(e)(s)
M. Michael Cusimano, PhD, M.D.
Institution(s) et partenaire(s)
St. Michael’s Hospital (University of Toronto), Ryerson University, SOSCIP
Description du projet
  • 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.
Année
2018
Statut
En cours
Titre
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
Financement du projet
IBM, Mitacs
Chercheur(e)(s) principal(e)(s)
M. James Green, PhD; M. Adrian Chan, PhD
Institution(s) et partenaire(s)
Carleton University, SOSCIP, Centre de réadaptation de L’Hôpital d’Ottawa
Description du projet
  • 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.
Année
2018
Statut
En cours
Titre
Safe Harbour for Military, Veteran and Family Health Research Data
Financement du projet
IBM, Mitacs, La Patrie gravée sur le cœur
Chercheur(e)(s) principal(e)(s)
M. Patrick Martin, PhD
Institution(s) et partenaire(s)
Université Queen's, The Centre for Advanced Computing
Description du projet
  • 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.
Année
2018
Statut
En cours

Initiative analytique avancée - Awarded Projects 2017

Titre
HERE4U Military Version
Financement du projet
IBM, Mitacs
Chercheur(e)(s) principal(e)(s)
Mme Heather Stuart, PhD
Institution(s) et partenaire(s)
Université Queen's, The Centre for Advanced Computing, SOSCIP, IBM Global Business Services
Description du projet
  • 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.
Année
2017
Statut
En cours
Titre
Using fMRI machine learning as a predictor of PTSD phenotype and treatment outcomes among treatment-seeking CAF members, veterans, and civilians
Financement du projet
IBM, La Patrie gravée sur le cœur, Mitacs
Chercheur(e)(s) principal(e)(s)
Mme Ruth Lanius, PhD; M. Don Richardson, M.D.; M. Nicholas Coupland, M.D.
Institution(s) et partenaire(s)
Western University, University of Alberta, Lawson Health Research Institute, Homewood Research Institute, SOSCIP
Description du projet
  • 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.
Année
2017
Statut
En cours
Titre
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
Financement du projet
IBM, Mitacs
Chercheur(e)(s) principal(e)(s)
M. Don Richardson, M.D.; M. Alexander Singer, M.D.
Institution(s) et partenaire(s)
Western University, University of Manitoba, Université Queen’s, The Centre for Advanced Computing, Calian
Description du projet
  • 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.
Année
2017
Statut
En cours