What is it about?
The twin necessities of keeping society going while maintaining social distancing and processing immense volumes of information to find ways of beating the pandemic have fast-tracked the digitisation and automation of processes. Within this shifting landscape, there is great potential for artificial intelligence (AI) and machine learning (ML)—combined with the internet of things (IoT), augmented reality, and 5G networks—to transform healthcare research and practice. Artificial intelligence can cost-effectively make systems logistically efficient, analyse large volumes of data, provide early warning systems for the disease, rapidly extract patterns from extensive information on symptoms, trials, etc., and quicken drug discovery, among other things. But studies also show that our AI technologies are not nearly as advanced as they need to be in order to truly achieve this potential. Without sufficient training data, predictions on infection rates and outcomes are not always accurate; there are privacy and ethical concerns where sensitive data are involved; existing inequalities and biases in training data can become amplified; and so on. This review collates research on the potential for using AI in healthcare during the pandemic, the concerns today, and future directions in the post-COVID new normal.
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Why is it important?
The digitisation brought on by the COVID-19 pandemic is irreversible. The integration of promising technologies like AI, ML, IoT, and big data with the healthcare sector could provide us an upper hand in disease management not only during COVID-19, but for future pandemics and other areas of healthcare. Understanding the current state of these technologies, their potential, and avenues for improvement are the first steps to their successful utilisation. KEY TAKEAWAY: AI has the potential to revolutionise healthcare. But for this to happen, our AI technology first needs improvement.
Read the Original
This page is a summary of: Chapter 12 AI in COVID-19 era, infodemic, and post-COVID-19 era, October 2021, De Gruyter,
DOI: 10.1515/9783110717853-013.
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Resources
How optical engineering helped us in the pandemic
Optics has contributed to improved infection control, diagnostics, and therapeutic development.
Making microscopes affordable with a single lens and machine learning
While single lenses have difficulty focusing different colors, they can take detailed single-color images. By adding color to these images using machine learning, this study could make low-cost microscopes a reality.
Detecting multiple COVID-19 signatures at the single molecule level
The new sensing device designed by the authors can help us detect and prevent the spread of COVID-19 as well as other infectious diseases.
Internet of medical things: How can it help during pandemics?
The cost of healthcare services is growing worldwide. Developing IoMT and addressing its shortcomings will help ensure better medical care during the COVID-19 pandemic and beyond.
Switching targets from virus to host: an alternative approach for drug development
Targeting the host instead of the coronavirus can help develop more successful therapies with fewer side effects.
New sensor makes virus testing quicker and less invasive
Access to fast, accurate, and affordable diagnosis of COVID-19 infection is essential to contain the spread of viruses and prevent major outbreaks. A new biosensor could help reduce the seriousness of current and future viral infection outbreaks.
Rapid advances in diagnosis of COVID-19
New types of testing lend themselves better to cheap, quick, hand-held devices; smartphones are also helping to improve testing as well as things like monitoring and contact tracing.
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