Predictmedix partners for clinical research with group led by Dr Samira Rahimi, an assistant professor at McGill University

Predictmedix partners for clinical research with group led by Dr Samira Rahimi, an assistant professor at McGill University

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Predictmedix Inc. (CSE:PMED) (OTCQB:PMEDF) has announced that it is partnering for clinical research with the research group led by Dr Samira Rahimi, an assistant professor in McGill University's Department of Family Medicine. The company said it will be working with Dr Rahimi's research group for its three industry verticals which include screening for infectious disease-associated symptoms, screening for cannabis/alcohol impairment along with mental health screening technologies which are being developed by the company. Professor Rahimi is also an associate member of McGill's Electrical and Computer Engineering Department, and an affiliated scientist at the Lady Davis Institute for Medical Research of Jewish General Hospital. READ: Predictmedix hopes to roll out its telemedicine platform Mobile Wellbeing in first quarter of 2021 "We are extremely excited with the partnership with Dr Samira Rahimi's team. Dr Rahimi is one of the most recognized AI - healthcare scientists in Canada and we look forward to with her and her research team for our 3 major verticals.", said Dr Rahul Kushwah, COO of Predictmedix Inc.in a statement. Speaking of the partnership, Dr Rahimi commented, "My team and I are looking forward to working with Predictmedix team. Predictmedix is one of the young and leading AI companies which aims to improve our healthcare system through innovative and cutting-edge digital health technologies." Dr Rahimi completed her postdoctoral training at Family and Emergency Medicine Department of Université Laval, and her doctorate studies (in Industrial and System Engineering with a focus on health care systems) at Mechanical Engineering Department of Université Laval. She is the recipient of numerous scholarships, fellowships, and awards among them the 2015 Canada Women in Engineering award of IEEE. With an interdisciplinary background, she is interested in the development, evaluation, and implementation of clinical decision support tools and patient decision aids, as well as integrating human-centred AI tools in primary health care. Her work as Principal Investigator has been funded by the Fonds de recherche du Québec - Santé (FRQS), Natural Sciences and Engineering Research Council (NSERC), Roche Canada, Brocher Foundation (Switzerland), and the Strategy for Patient-Oriented Research (SPOR)-Canadian Institutes of Health Research (CIHR). Predictmedix is an artificial intelligence (AI) company developing disruptive tools for impairment testing and healthcare. It is intended that the company's cannabis and alcohol impairment detection tools will be used across various workplaces and by law enforcement agents. Its technology uses facial and voice recognition to identify both cannabis and alcohol impairment by utilizing multiple features along with numerous different data points. Testing does not require any body fluids or human intervention, thereby helping to remove human error and the potential for discrimination and prejudice. The company is also developing AI-based screening for the healthcare industry. The recent advent of the coronavirus (COVID-19) pandemic has placed unprecedented stress on the global economy and highlights the need for tools to help screen mass populations for infectious diseases, with the hope of preventing pandemics in the future. In turn, Predictmedix s expanding its proprietary AI technology to screen for infectious disease symptoms. Additionally, psychiatric disorders such as depression, dementia and Alzheimer's disease can carry a significant burden and early identification is the key to better management. To help address this, the company is also expanding its proprietary AI technology to screen for psychiatric and/or brain disorders such as depression, dementia and Alzheimer's disease.  Contact the author at jon.hopkins@proactiveinvestors.com

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