Top 3 Projects from the “Hack the Crisis” Hackathon
In March (17–22.03.2020) a hackathon focused on solving problems related to the COVID-19 virus pandemic took place. There were around 200 ideas submitted and 10 of them were awarded a prize. We’ve selected the 3 we liked the most.
Detecting COVID-19 on X-rays with deep learning
We would rather call the project “Diagnosing COVID-19 based on X-ray images using deep learning” to be more precise. Anyways, one of the problems with COVID-19 is that infected people may show no symptoms of the disease. As resources for medical examination are very limited, such people have very little chance to be diagnosed and properly quarantined.
To solve this problem by ensuring easier access to examination, the team proposes an AI model that uses the x-ray images of lungs to diagnose if they are infected or not. By using an automated system, both the time and personnel required for analysing x-ray images could be notably reduced. It would allow for more people to undergo such examinations in a shorter time.
Unfortunately this idea is difficult to implement, at least at this moment, due to the lack of data required to train and evaluate such AI models. X-ray images, publicly available at the time of training, were presenting patients in serious condition where the infection was obvious. It could be the case that early stage development diagnosis based on the visual inspection of x-ray images of the lungs is inaccurate or less effective than other methods.
Still, we believe that if the required data would be available, then work on this approach should be continued. If extensive evaluation would show that the solution provides an efficient tool for diagnosis, it would not only be helpful during the epidemic but also in the future in every case where a similar approach could be deployed.
Medy — be rewarded for prevention ✨
Disinformation and a lack of knowledge on how to prevent the further spread of disease on the individual level are definitely unfavorable when fighting an epidemic.
The team working on Medy proposed a web platform aggregating verified news related to the epidemic of COVID-19, sharing tips about individual actions that everyone should be performing to stop the spread and stay safe, as well as a system for rewarding users who perform such actions.
We see the potential for using AI-based solutions in this project. Currently the team assumes that the verification of the news that can be published on the platform would be a manual process. Fake news detection is one of the most popular topics of research in Natural Language Processing. Automation of the verification process, or at least a part of it, would shorten the time between the submission of given information and its publication.
EpidemicApp
In Poland, patients with symptoms of a disease should report it to a sanitary-epidemiological station by phone. The capacity of such a system is very limited and only a fraction of reports can be processed in a given time, meaning that many patients must wait on hold or redial later without any guarantee that they’ll succeed.
The team proposed an online submission system for such reports that could later be processed by the personnel of sanitary-epidemiological stations. This idea would certainly reduce the current burden by the simple fact that in a phone-based system a single operator is required for every single patient. In the online solution, this capacity is limited only by the available transfer and processing power of the servers running the system.
Although the application would massively improve the situation of reporting, the reports still must be processed to decide if a patient is in a high risk group or not. This could be automated by AI. A model could use data from filled forms, even unstructured free form text data, to assess the probability of infection in each case. Documents with the highest probabilities would then be assessed by qualified personnel. Automating the process of initial verification would allow us to identify potentially infected persons much faster and undertake adequate action.
If you want to read more about AI, check out our site at Tooploox: https://www.tooploox.com/ai
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