Entries by Valerie Driessen

Cancer Prediction is the Pathway to Prevention

Examining the benefits of using a systems-based approach to predict and control the evolution of cancer through preventative pathways Oncology research exposes cancer as a dynamic disease that results from complex interactions between multiple scales of genetic, environmental and constitutional characteristics that are unique to an individual. Currently, the full scope of determinants that cause […]

Covid-19: Worldwide Viral Infection Model

Examining the benefits of using Universal Dynamic Engine (UDE) to manage Covid-19 patient risk and critical treatment load. When news broke of an obscure respiratory disease emerging from the Wuhan market in early January, few imagined that in just over 2 months the world would be facing the worst pandemic since Spanish flu in 1918. With […]

Advancing Economic Forecasting and Risk Analysis Models to Meet Demands of the 4IR

Managing dynamic complexity will pave the way for a more prosperous and efficient economy that operates with less risk and better predictability. Economic systems that operate through a constantly expanding number of dynamic interactions have become too complex to fully represent using popular econometrics and economic modeling methods. When multiple functions of economy are connected […]

URM Forum Launches to Solve Risk Management Problems of Fourth Industrial Revolution

The URM Forum, which will serve a global community of experts and practitioners who are committed to developing a more scientific, cross domain approach to identifying and managing operational risks that increasingly threaten business performance due to the dynamic complexity of our modern world, launched today. Current operational risk management practices are placing businesses in jeopardy. […]

New Book from Dr. Abu el Ata Offers A New Framework to Predict, Remediate and Monitor Risk

The Tyranny of Uncertainty explains why traditional risk management methods can no longer prepare stakeholders to act at the right time to avoid or contain risks such as the Fukushima Daiichi Nuclear Disaster, the 2007-2008 Financial Crisis, or Obamacare’s Website Launch Failure. By applying scientific discoveries and mathematically advanced methods of predictive analytics, the book demonstrates how business and information technology decision makers have used the presented methods to reveal previously unknown risks and take action to optimally manage risk.