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How AI Is Transforming the Way Doctors Diagnose and Treat Covid-19


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When Covid-19 began spreading across the globe in 2019, AI was on hand to assist, largely due to an abundance of “big data” and access to potent computing power.

This would not have been possible to the same extent even ten years ago. In recent times, the key advantage of AI-based systems is that huge amounts of data can be analyzed quickly and with surprising accuracy. The pace of processing power and investment in AI has driven a new generation of AI machine learning, as has been evident during the Covid-19 pandemic.

Nowadays, AI is already transforming the way medical professionals diagnose and treat coronavirus — and various other non-related diseases. Indeed, AI is also playing a major role in tracking the spread of Covid-19 and assisting in the development of new treatments and vaccines, boosting our ability to counteract the virus and fight future outbreaks.

Doctors can now take large data sets and run these at great speed through algorithms to establish patterns, either to make a fast and accurate diagnosis or to analyze the effectiveness of potential treatments. Cross-referencing data sets from around the world at this scale and speed would simply not have been possible in the past. 

As a result, the Covid-19 pandemic has catapulted the importance of AI into the mainstream. Real-life, practical applications for the technology are now clear for all to see. Further investment into AI and machine learning will no doubt further society’s ability to detect, track and react to future virus outbreaks as and when they appear.

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The DECOVID project is just one example of schemes to bolster the use of AI in medical care. This U.K.-based research effort comprises lead clinicians, AI specialists, NHS trusts and academics, bringing a truly multidisciplinary approach to the field. Continuing innovation is seen as the cornerstone of tackling future pandemics.

Below is an overview of how AI and machine learning is helping doctors and other professionals diagnose, treat, monitor and solve the ongoing Covid-19 crisis.

Faster diagnosis of patients

One of the advantages of AI and machine-learning algorithms is the speedier diagnosis of coronavirus in medical settings. This is particularly evident during chest screening of patients suspected of having Covid-19. The automatic reading of x-ray scans by advanced AI/ML systems helps assess the severity of the disease with encouraging precision. While not 100% perfect, these methods free up vital time for medical professionals and enable doctors to make quicker decisions. They can also assist in the faster diagnosis of other similar non-Covid related diseases.

Selection of new treatment methods

Discovering new treatments and ways to overcome Covid-19 is the key to getting the pandemic under control. AI plays a significant role in assessing the suitability, safety and reliability of different treatment approaches. Machine-learning systems also greatly assist in the drug-discovery and vaccine-development process. This is done by leveraging big data sets and cross-referencing these with clinical data to determine efficacy. Without these advanced data-processing methods, drug trialing and assessment would take far longer in situations where time is of the essence.

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Risk assessment of patients

AI has shown its importance in assessing the level of risk populations and patients have to coronavirus. By analyzing a person’s probability of symptomatic infection based on different demographics, such as pre-existing conditions, age and other factors, doctors can vastly improve their ability to protect the most vulnerable. Similarly, tools like the EpiRisk platform have also been instrumental in monitoring the risk of infection spread via airline transportation, helping countries better tailor their travel policies and protect their healthcare systems.

Better triage of suspected cases

With scarce resources in medical settings, AI is assisting doctors to triage patients based on their level of disease risk. By using vast quantities of collated data from across the world, doctors can assess who is more likely to require treatment first, based on age, gender, ethnicity and numerous other factors. Priority treatment based on hard data means that patient outcomes are vastly improved and healthcare providers can better manage their ability to cope with challenging circumstances. This triaging of patients is especially vital during pandemics, where the speed of admission and treatment can make the difference between life and death.

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Tracking the pandemic spread

Closely monitoring the spread of Covid-19 from its initial detection in Wuhan, China, to full pandemic was crucial in understanding the ferocity of the virus. AI was able to predict with great accuracy the projected spread of the virus and assist with vital contact tracing. The BlueDot system, for example, utilizes big data and machine learning to assess the risk level of viruses and predict future pandemics based on early virus identification. This system was vital in the early stages of the pandemic, spotting the tell-tale patterns that are the hallmarks of a wider pandemic.

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