With Covid-19 pandemic raging all around the world causing harm to public health and livelihoods, this is a good time to strategize how AI can be used effectively to help the health care industry to fight this pandemic in particular and overall preparedness in general. The 3 main areas that we believe AI can help are,
- Automated monitoring of mask and other Personal Protective Equipment (PPE) compliance to prevent the spread of infections.
- Data aggregation and building predictive models to identify potential hot spots for the spread of infection.
- Building AI-based tools to act as a physician’s aid in diagnosis and treatment of Covid-19 positive patients.
Each of these three use-cases is described in detail below:
1. Automated monitoring of mask and other Personal Protective Equipment (PPE)
Computer-vision-based AI models can be trained to detect if humans are wearing PPE-like masks and if health care workers are wearing PPE suits, gloves, face-shield etc., Experts all over the world concur that wearing face masks is a simple yet important way to prevent the spread of infection. However, monitoring the PPE usage among the general population is a vexing problem. Lack of monitoring will lead to a lack of PPE compliance and will risk an emergence of the disease spread that the world has worked hard to contain so far. Optisol Datalabs team are experts in building such AI models for PPE monitoring, and compliance in industrial space even before this pandemic took over the world. In fact, we are one of the only AI service providers who have successfully implemented PPE compliance monitoring and tracking in industries to improve health and safety. We are re-training such models currently to detect healthcare-related PPE like masks, gloves, safety suits and face shields.
The model we train is optimized to run in edge devices like cellphones enabling rapid deployment of such models without investing in expensive hardware. Such cellphone turned AI devices can be programmed to send safety violations to the concerned authorities to quickly take preventive actions. The detailed process flow on how to train and deploy such AI models is described in the diagram below.
A demo of our Computer Vision-based AI model trained to detect masks, safety suits, face shields and gloves is published at this link in our YouTube channel.
2. Predictive models to identify potential infection hot spots
Daily data on current Covid-19 positive cases are published in various news outlets. It is possible to collate all these data and build a model that can predict the likely hotspot of the infection to warn the residents in those areas to exercise caution. Google and Apple are about to publish updates to their platforms that allow monitoring of the movement of the smart phone users in a way that does not violate the privacy of the users. This will allow a more granular collection of real-time data to build such predictive models with increased accuracy and granularity. Such models are effective tools for public health organizations and individuals to get access to accurate data and to prescribe the least intrusive policies that allows resumption of economic activity at the same time reduce the risk of infection spread. We have extensive experience in building such time-based predictive models. We are currently working on building a model from the publicly available data right now.
3. Models to act as physician’s aid in diagnosis and treatment
Another important use of Artificial Intelligence in healthcare industry is to build models that act as physician’s aid in disease diagnosis and treatment. There was a famous experiment conducted in the US where the AI can predict heart attack and stroke better than trained physicians (https://time.com/5784090/ai-heart-attack-stroke). AI models can operate on a large number of parameters that even trained physicians cannot always reliably compute to make their decisions. In such situations, Artificial Intelligence becomes a valuable tool at the physician’s disposal for to increase the accuracy of the diagnosis and effectiveness of the care. There has been a lot of interest in just using chest x-rays to predict Covid-19 and there are a lot of service providers who claim to build an accurate diagnostic tool to detect Covid-19 from a chest x-ray. Such claims are not scientifically validated, hence cannot be relied on up as effective diagnostic tools. Such hype in fact causes skepticism in using Healthcare AI Solutions amongst health care providers. This is quite unfortunate. Because AI is proven to be an effective diagnostic aid if used correctly. Chest x-rays are but one data point in the diagnosis of the disease. There are other effective data points like travel history, place of residency, potential contacts (neighbors, family members, colleagues) with a positive diagnosis, other symptoms being experienced like fever, cough etc., staying in a nuclear family with mixed age group members, past health history of pulmonary diseases, etc., When all these data points are combined and fed to an AI model, we will greatly increase the predictive accuracy of the tool. In fact, these data can be collected from the patient at their homes and they do not even have to visit a hospital and potentially risk spreading the infection.
Conclusion
These 3 use cases span infection control, monitoring the spread of infection for effective public policies and diagnosis and treatment of the disease. In our opinion, Artificial Intelligence is somewhat underutilized in how it can be effectively used to help mankind traverse the current pandemic successfully with the minimum loss of life and property. We are at the forefront of developing and deploying these AI models. We are the leading Healthcare AI Software Solution Companies In US | Australia
