The impacts and potentials of AI on infectious diseases
Pathogenic microorganisms are the cause of infectious diseases. The way they spread however, may vary: as they can spread directly, which means human to human contact. They may also spread indirectly, which means environment to human or vector to human; which means through an organism like a mosquito that transmits a disease from an infected person or animal to another.
The problem with infectious diseases is that some of them can be deadly. They are contagious and their incubation periods; which may last days or weeks, can have no obvious symptoms. In addition, the lack of knowledge as well as having no means to the detection of said diseases can result in catastrophic results; case and point, Covid-19. The pandemic can’t be predicted using traditional statistical models, these models are in need of development and elaborate approaches, so they can be used to help when making important decisions. Currently, the applications of AI and ML methods have started to be applied when investigating covid-19, according to various recent studies.
The pandemic is a current dramatic example of infectious diseases; most cases were unprecedented and it had led to deaths. Covid-19 is highly unpredictable; almost all the traditional epidemic models based on the data that was early given, had tuned out to be wrong. All of them, unfortunately failed to predict the progression of the pandemic. The traditional models don’t have the capability of neither reacting nor adapting when encountering unexpected factors or situations. They also don’t handle huge amounts of data well. On the other hand, AI would enable the machines to act and react in a much better way, regarding the pandemic evolution and progression as it can withstand the immense data surges.
Applying AI to infectious diseases, especially covid has increased and started to become a popular method. Both AI and ML can be integrated with traditional models, so that they can infer critical parameters of the disease. This can be done through reported case data, which ultimately will result in more accurate results. Seeing that AI and ML are constantly developing, it is believed that they are a vital tool in epidemiology as they are the only tools with the potential of numerous breakthroughs in the field. Integrating AI with other computational and statistical approaches can be the end to all our problems.