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How artificial intelligence can improve decision making for government and healthcare CIOs amidst Coronavirus pandemic

Artificial intelligence capabilities will be most effective when applied in full collaboration between IT leaders and medical specialists

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DQINDIA Online
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Executives responsible for artificial intelligence (AI) strategy, particularly CIOs and CDOs in governmental and healthcare organisations, should leverage AI in five core areas to improve decision making during the coronavirus pandemic, according to Gartner, Inc.

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“In the fight against COVID-19, AI offers an important arsenal of weapons,” said Erick Brethenoux, research vice president at Gartner. “It allows predictions to be made about the spread of the virus, helps diagnose cases more quickly and accurately, measures the effectiveness of countermeasures to slow the spread, and optimises emergency resources, to name a few. The power of AI should not be ignored or only partially leveraged, so long as it is applied in ethically responsible ways.”

Five areas where using artificial intelligence to combat Coronavirus will have the most impact

Early Detection and Epidemic Analysis

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AI techniques are used to understand, analyse and predict how and where the virus is spreading or slowing down.

Automated contact tracing, for example, is used to build detailed social interaction graphs by analysing a myriad of citizen data such as mobile phone locations and public facial recognition and backtracking the movement of people to identify the likely virus source. Individuals who encountered the source can then be notified, tested or quarantined.

“Other AI applications that fall within this area include epidemic forecasting and monitoring the development of herd immunity. Such capabilities are obviously highly relevant in the short term as society tries to ‘flatten the curve’ and minimise the burden on our healthcare systems, but they are also important in the long term if new, hopefully smaller, outbreaks reoccur,” said Mr Brethenoux.

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Containment

Considering the huge societal and economic impact of ‘one-size-fits-all’ measures such as lockdowns, collaboration with non-IT experts is paramount when applying AI to containment efforts.

“Behaviour analytics derives new insights by accounting for the dynamics of human behaviour, culture and individual thinking to answer questions around social distancing compliance or the emergence of unwanted group behaviours,” said Pieter den Hamer, senior research director at Gartner. “Law enforcement can predict where and when people may not adhere to stay-at-home orders or social distancing through predictive enforcement and dispatch enforcement units accordingly.”

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Triage and Diagnosis

The use of AI-enabled self-triage has already gained popularity as telehealth practices, including virtual health assistants, were made available to help people identify if they are possibly infected and what the appropriate next steps are. Augmented medical diagnosis and triage are also key AI capabilities that help in this area.

“AI is known to improve the accuracy of certain diagnoses if augmented with human judgment, especially in more complex cases,” said Mr den Hamer. “Prognostic modelling or predicting how the disease will likely develop in patients, can also be used to improve treatment recommendations. The fact that AI has a role to play in assessing patient risk and prognosis is not something to overlook, especially when there is a possible shortage of medical professionals.”

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Healthcare Operations

AI plays an important role in streamlining healthcare operations and optimising scarce hospital resources during a pandemic. Healthcare CIOs and CDOs can use predictive staffing to improve personnel allocation by analysing anticipated patient numbers and their individual prognosis, and cross-referencing them with the availability of qualified medical staff, materials, and equipment.

“Remote patient monitoring and alerting with the use of AI also allows patients to stay at home, lowers the burden on hospitals, and enables a better understanding of how symptoms develop over time,” said den Hamer.

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Vaccine Research and Development (R&D)

AI graphs and natural-language processing (NLP) can enable medical researchers to scour through many thousands of relevant reports to draw connections between data at an unprecedented pace. Augmented vaccine R&D also identifies coronavirus countermeasures including those that have already been tested on humans.

“Healthcare CIOs and CDOs should explore every avenue of AI to fight COVID-19 using an ongoing and systematic process of AI application identification and prioritisation. Technologists should not overestimate their ability to understand what makes sense from public health and medical perspective and then work with healthcare professionals to create and actively advertise an open marketplace that shares AI applications, models and data transparently,” said den Hamer.

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