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Right impact at the right time

AI and Data Science solutions against COVID-19

Datasets and R&D directions for today’s pandemic and future public security

Alexandr Honchar
Mar 12 · 7 min read

During the last couple of months, the COVID-19 outbreak more known as “coronavirus” or “Wuhan” was the most discussed topic online and on the empty streets. We had different opinions about it from conspiracy theories to comparisons with regular influenza, but today we are in front of a fact that COVID-19 is a pandemic and somehow we need to protect from it, stop its spreading and, finally, fight it.

As a person, who works in the AI field, in this blog, I’d like to share some directions where I and my colleagues can work to help public and private sectors all over the world. I hope that entrepreneurs and members of the government will see the opportunities not only for the temporary getting rich schemes or control of the citizens but as important parts of a strategical roadmap to improving public health and security.

Public Health Surveillance

The main danger of coronavirus is its spreading speed. That’s why governments put such measures as quarantines of the whole country because they can’t control the local outbreaks efficiently. One of the most straightforward steps towards the detection of sick people in the analysis of CCTV cameras that are already around us and finding people who show severe symptoms of the diseases and isolate them, who they contacted with and disinfect the corresponding surfaces. At Neurons Lab we have developed a demo solution, which you can see on the video above. The dataset to start research by yourself is available here.

Remote biosignal measurement

Some of the symptoms as temperature or pulse are very important to ignore them and rely only on the visual appearance that might be confusing. But of course, we can’t stop any person to measure their pulse, blood pressure or temperature. Maybe we could do it remotely somehow? Actually, there are some developments in computer vision that can estimate pulse and blood pressure based on facial skin analysis:

Concerning the body temperature, there are some developments as well, but in this case, for practical use, we would like to look into the direction of thermal imaging, not the regular cameras. At least for now.

IoT and wearables

Of course, measurements like pulse is much more comfortable and convenient to gather from the wearable devices like fitness trackers and smartwatches that almost everybody of us already has. But was has pulse to do with this? It can tell about physical, emotional state, maybe about arrhythmias, but influenza? Some researches state, that heart rate variability analysis and its deviations from the normal state can show early patterns of flu and, in our case, coronavirus.

Chatbots and communication

Apart from “scanning” people in public, we might want to rely on their consciousness and self-assessment. If you can measure your temperature and pulse daily and record your coughs time-to-time, you also can add it to your diary. Then, either doctor remotely, or an algorithm can recommend you to stay home, take some other preventive action or request the visit of the doctor if the symptoms are too severe. One of such solutions you can check out here:

Social media and open data

Maybe you’re not the fan of having a health diary or sharing things online, but there are a lot of us that share it with the complete strangers in Instagram or Twitter. This data is helpful for more broad analytics of how far the disease went away. With the information about the users, we also can analyze the social networks graph and try to estimate what social groups are at risk of being contagious. Concerning the data, you all know where to get it and what public APIs are :)

Canadian startup BlueDot analyses much more than just social media data: for example, the worldwide movements of more than four billion travellers on commercial flights every year; human, animal and insect population data; climate data from satellites; and local information from journalists and healthcare workers, pouring through 100,000 online articles each day spanning 65 languages.

Mathematical modeling

Obviously, before coronavirus, we have encountered many other infections diseases and studied the rules of their life cycle. We have created mathematical models that can describe the evolution of the disease in the population and we can re-use them, again and again, to explain the novel outbreaks and even predict at which stage they are (aka “how bad everything is”). The good starting point for your own analysis of the coronavirus cases all over the world is here, alongside fitting the logistic curve in order to understand at which point exactly the situation is right now in Italy (alongside with a tutorial on getting the up-to-date data):

Also, it is important to model not only the virus evolution itself but also the countermeasures that are used. Instead of blindly closing the whole border, mathematical models can help us to understand how to allocate prevention resources more focused and optimal in the early stages of the outbreak. Check out mathematical optimization application in the paper below; on the image: comparison of no measures (A) vs other pure mathematical-based measures.

Automated diagnostics

COVID-19 has opened to us another problem of today healthcare: it doesn’t scale when the number of patients grows quickly (actually tired doctors work only worse) and in general, the number of false-negative diagnoses is pretty high. Machine learning diagnostics doesn’t get tired and scales naturally just with the increase of the computational powers. We already see how deep learning-based lung image analysis works well in a current pandemic as well:

Drug development research

Last but not least, apart from detecting and preventing the spreading of the diseases, we need to think about the creation of the vaccines on the scale. One of the important steps towards its creation is understanding the structure and nature of the virus we’re fighting against. DeepMind with their experience in protein folding analysis also made their step in predicting the protein structure of the virus and made it open-sourced.

The dataset on COVID protein structure and other flu for your own analysis you can find here:

Last but not least, AI can help in the analysis of already published academic works on viruses as SARS and current COVID. You can find a related dataset on Kaggle:

Conclusions

Of course, most of the described approaches are very research-y and require major efforts to be really useful for most of the people. However, I find most of them indeed vital parts of the whole ecosystem for 360-degree defense:

  • local outbreaks detection with video surveillance, remote biosignal measurement, and wearable data analysis;
  • efficient treatment on a scale with the help of AI-based diagnostics of the samples;
  • region-level analytics with social media analysis and chatbots;
  • global development predictions with mathematical modeling based on the local and regional data updated regularly;
  • meanwhile, drug development is boosted with AI-based simulations and molecule generations.

At Neurons Lab we are investing resources in several directions described above. You could see a demo of video surveillance analytics for symptoms detection and we’re working on mathematical models of infections spreading as well. We’re inviting for the collaboration interested parties, let us know!

P.S.
You also can connect with me on the Facebook blog or Linkedin, where I regularly post some AI articles or news that are too short for Medium and Instagram for some more personal content :)

Data Driven Investor

from confusion to clarity not insanity

Alexandr Honchar

Written by

🇺🇦 🇮🇹 AI entrepreneur and practitioner. Consulting, giving talks, teaching, writing. Co-founder, CTO @NeuronsLab | Partner, Architect @Mawi

Data Driven Investor

from confusion to clarity not insanity

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