3 Strong Proofs of How Technology Challenged COVID-19

3 Strong Proofs of How Technology Challenged COVID-19

In the light of COVID-19, digital transformation is accelerating at an unprecedented rate from the selection of the AI vaccine applicant to the mass roll-out of virtual consultations. This new series examines the various ways in which pharmaceutical and health technology companies react to the pandemic.

When the pandemic passes, it is estimated that in just a few months healthcare systems would have changed for a decade.

3 Strong Proofs of How Technology Challenged COVID-19

It once seemed impossible to redefine the way care is developed, delivered and received. But health technology and digital health prove their worth and influence the future in the face of necessity.

E-Learning

As the pandemic continues, medical practitioners face a range of educational challenges. It is all vital to disseminate COVID-related learners, to develop them continuously, and to ensure that retired and retrained personnel are ready to return or start work.

Digital learning is booming, as is true across sectors. With large meetings out of question, annual conferences will be moved online, resulting in an increase in attendance by many organizations and associations.

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E-CARE

E-Care has long been hailed as an overly extensive service solution, especially for people who treat chronic illnesses.

The routine monitoring of video calls can offer greater comfort for patients and free time for those who need or prefer personal appointments. The following can also be done. But it was slow and fragmented until now to be incorporated into routine care.

In April, The Lancet reported 10 times more virtual consultations in the US as providers tried to reduce health-care risks.

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Big Data and AI

This is not the first time the world has been faced with a global pandemic – however, it is the first time that such a wealth of data is collected quickly in the healthcare community. Many believe that this gives AI and Big Data a perfect chance to prove their value.

The COVID-19 Open Research Dataset (CORD-19) of Allen Institute, which helps researchers to keep up with the purely public research volume, is a good example of this.

The database, which consists of tens of thousands of articles and is produced daily, is readable by the machine and enables researchers to create and implement their own algorithms for natural language processing for access to the latest information.

There it does not stop. AI can facilitate the collection, risk assessment and decision-making of epidemiological data in real-time and can design and implement public health interventions. It can help clinicians identify diagnostic and predictive characteristics and help researchers speed up the selection of vaccines and treatment candidates.

He said: “This is used to trace the spread of the virus in real-time, and plan and lift interventions for public health, to track its effectiveness, to repurpose ancient compounds and to discover new medicines and to identify potential candidates for vaccines and to improve communities responses to the virus.”

“While these emerging approaches allow data analysis and interpretation, these are used together with classical surveillance: the latter reveal hidden trends and patterns which can be used to develop predictive modelling.”

3 Strong Proofs of How Technology Challenged COVID-19

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