We're pleased to announce the launch of AI4PEP-TDP4 project titled, "Telehealth data, predictions, pandemic prevention and preparation". This initiative is a product of the collaboration of researchers from the University of Alberta, University of the Philippines Diliman, National Center for Mental Health, World Association for Psychosocial Rehabilitation, and the University of San Agustin. It aims to develop and implement a disease surveillance system in underserved and low-resource settings in Western Visayas, Philippines.
Together with our partner communities, we envision that this project will pave the way for healthcare services to reach underserved communities that need them the most.
#WAPR #AI4PEPTDP4 #AI4PEPLaunch #USACFI #YorkU #IDRC
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Understanding the Causes of Antimicrobial Resistance (AMR)
Antimicrobial Resistance (AMR) has emerged as a pressing global health threat, endangering the effectiveness of antibiotics and other antimicrobial agents that are essential for treating bacterial infections.
Quantifying Consequences through a Bayesian Regret Analysis of Computational Models
From social policy to healthcare, computational models have been used as a crucial step in guiding decision-making. But depending on how they are applied, the conclusions drawn from the data may prove beneficial or disadvantageous.
Keywords: Bayesian Regret, Vulnerable Population, COVID-19, Mathematical Model