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27 Jan 2021

Trending topics in AI for 2021

With AI and machine learning having an increasing importance on the way we manage our healthcare systems. What new developments can we look forward to?  


AI and robots that support, diagnose and treat people are already in homes, workplaces and clinical environments all over the world and their usage is growing exponentially. Medcity News recently reported that “Even Covid-19 has not dampened the AI fire as 38% of technology leaders report that their AI investment plans are unchanged, and one-third (32%) say the pandemic has accelerated their plans.” Boston Children’s Hospital chief information officer Dan Nigrin further comments that AI applications that promote telehealth, for example, “are not necessarily Covid-related, but certainly the pandemic has accelerated the consideration and use of these kinds of tools.” 


For many healthcare leaders, accelerating these plans will create a more efficient pathway for working in clinical environments, as well as the ability to share information on a much grander scale but also much more quickly. As Whitney J. Palmer and Mina S. Makary, MD, state in 6 Trends to Watch in 2021: “One thing we will continue to work on, as a specialty, is how we can integrate this technology into our clinical workflow. Everyone is now thinking about how artificial intelligence will augment their performance to become better, quicker, and more accurate.” 


This is particularly true when it comes to diagnosing patients. Last year the BBC reported that “AI 'outperforms’ doctors diagnosing breast cancer”, Dominic King from Google Health said at the time: "Our team is really proud of these research findings, which suggest that we are on our way to developing a tool that can help clinicians spot breast cancer with greater accuracy." Expect stories like this to be commonplace in 2021, as diagnostics is seen as big growth area for healthcare.  


Accuracy in results is one of the biggest challenges facing AI currently if it’s to improve patient outcomes. However, due to the increased use of AI globally there is already discussions taking place on how to diagnose multiple diseases, at the same time! Some Radiology AI companies including DeepMind and Pr3vent have already designed devices capable of detecting “over 50 ocular diseases from a single retinal image.” There is a lot of potential for AI in radiological settings, but accuracy will be key with these algorithms. “Such issues could lead to a mistrust of AI tools by radiologists, which may in turn reduce their rate of implementation in medical settings.” 


To enable efficient analysis of patient scans, image recognition AI software should be able to combine and interpret data from different imaging sources to gain a better perspective of the patient’s pathology. However, there is still question marks surrounding AI’s current value proposition with many radiologists grading AI’s value below their expectations. That’s not to say that the technology is useless, but there is a lot more that needs to be done to improve the technology. 


What is certain, is that AI and machine learning has a lot of potential, and we will see healthcare institutions implement and test new devices throughout the year. Expect many interesting stories throughout 2021.

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