Dr Amir Talaei-Khoei refuses the effectiveness of AI to determine vaccine prioritization
Industry: Apps & Software
The mortality rate of COVID19 has not been impacted by the use of Artificial intelligence (AI) techniques.
Reno, NV (PRUnderground) March 2nd, 2021
Dr. Amir Talaei-Khoei and his team at the University of Nevada, Reno have developed data-oriented models that use AI to prioritize members of populations for receiving COVID-19 vaccines. The study found that AI, despite the existing hope, is not a right tool and cannot reduce the mortality rate of this infectious disease.
The team at the College of Business in the University of Nevada Reno (UNR) created an AI algorithm that could prioritize the group of population including vulnerable individuals to receive COVID19 vaccine. Dr. Talaei-Khoei has worked on the initial empirical evaluation of the algorithm and realized that the developed approach may not be effective in terms of reducing the mortality rate of COVID19.
“In developing the algorithm, we have been inspired by human neural networks and how they can represent the structure of a city, county or a town in terms of both population and physical structures,” said Dr. Amir Talaei-Khoei, an associate professor of Information Systems at UNR. The model replicates the physical locations as well as the population and the lifestyles.
Evaluating the model through simulation, Dr. Amir Talaei-Khoei and his team found little or no improvement in mortality rate of COVID-19. “After a careful digging into the results, we have realized there are more into Scio-economical parameters involved in COVID-19,” said Dr. Amir Talaei-Khoei. These parameters are influenced by the culture, value system and income level of individuals, which makes it difficult to collect data.
The algorithm developed at UNR is heavily dependent on the input data. In the same time, collecting data on Scio-economical parameters is time consuming and expensive. “Socio-economic factors also create uncertainly that harms the accuracy of our AI model,” said Dr. Amir Talaei-Khoei.
The team led by Amir Talaei-Khoei concluded that the AI model developed in this study cannot provide sufficient insights for public health officials and practitioners. They believe AI is extremely dependent on the quality of its inputs. In the case of COVID-19, the socio-economic factors play a significant role and that prevents us on having accurate prioritization of population for vaccine. “Conventional public health approaches and methods can be better choices to include Socio-economic parameters for drawing priority around populations to receive vaccines,” Said Dr. Amir Talaei-Khoei.
