Welcome to the ML4QI Lab, Stroke Innovation Lab

Our lab focuses on using machine learning for Quality Improvement in neurology and stroke care. The ML4QI Lab, PI: Dr. Houman Khosravani, is located in Toronto, Division of Neurology. Our lab's work is dedicated to Quality Improvement (QI) in several current areas of research:

• ML4QI - machine learning for bolstering current standards of care. We are leveraging machine-learning to enhance QI within acute stroke care in the inpatient setting. Our current work is focused on using voice as a biomarker - we call this Sonic Diagnosis.
• stroke resuscitation - our lab termed the work "stroke resuscitation", developed the protected code stroke protocol, defined the use of crisis resource management in stroke, and thus our focus is education and quality improvement during the code stroke process. We use CRM pricinples and have an active code stroke simulation program. This also includes our efforts within NICE (Neurovascular Innovations CollaborativE) as listed below.
• palliaitve care in acute stroke - we are passionate about providing maximal effective care and that includes integration of palliative care within stroke treatment; our lab works on the development of protocols for routine integration of palliative care as we define the scope of palliative medicine in acute stroke care.

Members of the lab also are involved in educational initiatives, a podcast on stroke education: Stroke FM Podcast, the official podcast of the Canadian Stroke Consortium.

Machine Learning 4 Quality Improvement (ML4QI) and the Neurology Quality and Innovations Lab (NQIL)

• We are also exploring the intersection of machine learning and quality improvement, utilizing voice-based technologies to refine our methods. We have expertise in deep-learning and processing of audio signals.

• Our pursuit of excellence extends to the cutting-edge field of machine learning. With support from T-CAIREM and SHSC, we are leveraging bedside physiologic recordings to improve the quality of acute stroke care.

• Machine learning as applied to quality improvement in stroke

  • 2024
    • Lab Members (continuing and joining):
      • Dr. A. Balachandar, Neurology, U of T, ML4QI in Stroke
      • R. Saab, U of T Med, AI4QI in Stroke, U of T, Med 3, Sunnybrook Research Institute
      • E. Nashnoush, MSc, U of T Data Science, Datathon co-founder, T-CAIREM, HQO
      • H. Mahdi, Western University, Med 2, Sunnybrook Research Institute
      • Dr. E. Adegunna, Neurology, U of T, ML4QI in Stroke
      • Dr. B. Tilley, Neurology, U of T
      • R. Dagli, CS2, U of T
  • 2023
    • Lab Members:
      • Dr. A. Balachandar, Neurology, U of T, PGY5 (PGY4 Project), ML4QI in Stroke
      • R. Saab, U of T Med, AI4QI in Stroke, Sunnybrook Research Institute
      • E. Nashnoush, MSc, U of T Data Science, AI4QI in Stroke, Sunnybrook Research Institute, T-CAIREM
      • H. Mahdi, Western University, Med, AI4QI in Stroke, Sunnybrook Research Institute
      • Dr. B. Sivanandan, Neurology, U of T, PGY4 Project, Palliative Care in Stroke
      • Dr. M. Mahendiran, U of T, Family Medicine (graduated), Palliative Care in Stroke
      • Dr. E. Adegunna, Neurology, U of T, PGY2
      • Dr. B. Tilley, Neurology, U of T, PGY1
  • 2022
    • Lab Members:
      • Dr. A. Balachandar, Neurology, U of T
      • R. Saab, U of T Med, T-CAIREM
      • M. Panchal, U of T Med, CREMS

Neurovascular Resuscitation - Neurovascular Innovations CollaborativE (NICE)

• Our lab championed the framework of crisis resource management in stroke simulation to optimize critical intervention metrics such as "door-to-needle" times. We are proud to be pioneers in the field and we published the first reframe of Crisis Resource Management (CRM) for stroke care care. We alsp developed the "protected code stroke" during the COVID19 pandemic, which was integrated into national and international guidelines, and downloaded over 27K times from the American Heart Association, Stroke journal's website. Our research aims to enhance care pathways and human performance factors for acute stroke patients through simulation of neurovascular resuscitation. We have introduced the concept of "neurovascular resuscitation," applying principles from medical and trauma resuscitation to stroke treatment - thereby reinstating the 'code' in code stroke.
• In 2023, Dr. Houman Khosravani and Dr. Christine Hawkes co-founded the Neurovascular Innovations CollaborativE (NICE), an initiative projected to contribute substantially to augmenting neurovascular care education.
• Our lab's portion of focus is the medical/neurocritical care efforts within NICE, while Dr. Hawkes helms the neurovascular and catheter-based aspects of hyperacute care and techniques.

Routine Integration of Palliative Care in Stroke

• Despite significant advancements in stroke care, a considerable number of patients still grapple with substantial morbidity and mortality. Recognizing this, we advocate for the routine integration of palliative care into stroke treatment. Compassionate and effective care forms the bedrock of the philosophy we advocate for in terms of expanding the confluence of palliative medicine and stroke care.

If you are a student with an interest in QI and experienced in research, or if you are an engineering or CS or MD student interested in clinical applications of machine learning in neurology please reach out.

Disclaimer

This GitHub repository is for educational purposes only and does not represent expert medical judgment or assessment. The tools and information provided herein are not intended for clinical use and should not be relied upon for medical decision-making. No duty of care is assumed by the contributors, and all individuals associated with this project are absolved of any medical-legal burden. The views and work expressed in this repository do not reflect the official stance of any affiliated academic/other institutions or hospitals where we work or study. Use at your own risk.