The 6th Annual Â鶹AV Clinical Innovation Competition and Awards Ceremony took place on May 11, 2023.
To watch the video recording of the event, .
Congratulations to all of our winners and finalists! Â
Image by Owen Egan/Joni Dufour.
Winner of the Hakim Family Innovation Prize
PL Signals
Lung fibrosis is a serious chronic and progressive disease with limited treatment options. TGF-beta is a potent pro-fibrotic factor, and its excessive action plays a central role in lung fibrosis. We have developed a novel anti-fibrotic biologic that traps TGF-beta with high specificity and efficiently reduces lung fibrosis in preclinical models and in vitro in patients’ fibrotic cells.
Anie Philip, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Shikha Chawla, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Kenneth Finnson, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Jini John, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Tenzin Kungyal, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV
Image by Owen Egan/Joni Dufour.
Winner of the First Marika Zelenka Roy Innovation Prize
CoreSlicer
CoreSlicer is a cloud-based AI platform that automates the measurement of frailty and body composition from clinically available medical images (CT, MRI, ultrasound). The insights provided by CoreSlicer empower clinicians to individualize the care of vulnerable older patients to prevent postoperative complications, fatal adverse events, and emergency readmissions.
Jonathan Afilalo, MD, MSc, Principal Scientist, Jewish General Hospital, Â鶹AV Philippe Marchandise, Lead Developer Ding Yi Zhang, Data Scientist & Medical Student Zara Vajihi, Machine Learning Engineer Magueye Diagne, Data Engineer Jeremie Abitbol, Strategic Analyst Ibrahim Mohamed, Full-Stack Developer Robert Viengkhou, Interface Designer Louis Mullie, MD, MSc, Prior Member Marc Afilalo, MD, Clinical Scientist
Image by Owen Egan/Joni Dufour.
Winner of the Second Marika Zelenka Roy Simnovation Prize
PeTIT VRÂ
PeTIT VR (Pediatric Trauma Innovative Training) is a virtual reality course designed to enhance the skills of healthcare students and providers in pediatric trauma care. By leveraging the immersive and interactive nature of virtual reality technology, PeTIT VR is able to provide a unique and effective training experience that increases the quality of care and safety for pediatric trauma patients.
Fabio Botelho, MD, Experimental Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Dan Poenaru, MD, Experimental Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Elena Guadagno, MLIS, Division of Pediatric Surgery, Montreal Children's Hospital Hamed Ranjbar , MSc, Experimental Surgery, Faculty of Medicine and Health Sciences, Â鶹AV
Image by Owen Egan/Joni Dufour.
Winner of the First-Place MI4 Innovation Prize
  & the Bereskin & Parr Innovation Prize
BacPen DIAGNOSTIC
BacPen DIAGNOSTIC is a medical device start-up focused on a real-time point-of-care approach for diagnosing bacterial infections. They have developed a technology using electrochemistry that allows detection and specifically quantification for bacteria and other biological moieties in liquid and solid specimens.
Geraldine Merle, Professor, Biomedical Engineering, Polytechnique Edward Harvey, Professor, Department of Surgery, Faculty of Medicine and Health Sciences, Â鶹AV Raphael Trouillon, Assistant Professor, Electrical Engineering, Polytechnique
Image by Owen Egan/Joni Dufour.
Winner of the Second-Place MI4 Innovation Prize
Curaforge
Curaforge aims to provide a low-cost and innovative solutions to make the stethoscope safer for healthcare workers and ultimately prevent healthcare worker exposure in the form of a medical device.
Sean Seltzer, Medical Resident, Faculty of Medicine and Health Sciences, Â鶹AV
Congratulations also to our finalist teams:
Image by Owen Egan/Joni Dufour.
CapmAI
CapmAI is a leading provider of AI-based diagnostic solutions for capsule endoscopy. Their goal is to minimize diagnostic errors, increase efficiency for gastroenterologists, and accurately identify the location of disease.
The current standard tourniquet consists of a strip of fabric fastened about a hemorrhaging limb, and a windlass to mechanically augment tightening. However, inappropriate tourniquet application, either in terms of applied pressure or excessive duration, may lead to ischemia, nerve palsy, exsanguination, and possibly amputation. SmartTQ addresses these issues by incorporating a vessel occlusion sensor and timer to monitor these salient parameters, providing key data to soldiers and doctors.
SPINORT is an algorithm driven smart garment that manages and prevents recurrent mechanical low back pain. The device captures personal motion and muscle activity data and calculates the amount of near-infrared energy needed to stimulate the deep back muscles and correct the spine posture, and as such improve physical movement.
Antonia Arnaert, Associate Professor, Ingram School of Nursing, Â鶹AV Swajan Paul, PhD student, Department of Experimental Surgery, Â鶹AV ZoumananDebe, Research Associate, Ingram School of Nursing, Â鶹AV
