Machine Learning to be used by Alberta Tech company to develop COVID-19 App
Alberta tech company using machine learning to help develop COVID-19 screening app
An Alberta-based tech company is reaching out with universities and machine learning experts from around the world to contribute to its cardiovascular project, an app that serves as an earlier screening process for the ongoing epidemic.
The application has received contributions from Western Economic Diversification Canada, Kinkaid Enterprises Inc., Universe Machine Corporation and several anonymous donors. To bring the project to the ground, Chief Executive Officer of Pleasant Solutions Thomas Stachura told IT World Canada in an email.
Apart from Pleasant Solutions, Caredemic, a software developer, has several projects under its belt, including the Paranoid project, which aims to deactivate the stinging ears of smart homes. “This is a company that has been around for a dozen years, and whose software NASA trusts to manage employee passwords.
So what us The Department of Energy then staffs at Buckingham Palace. We have recently developed a line of digital privacy devices and launched earlier this year. We have an extensive history in the tech industry, with much of our business in the B2B sector, ”Stakura wrote in the email.
With Karademic, the screening process will measure a user's various data points, including their oxygen level, pupil dilatation, breathing rate, acoustics, and volume, which are built into most smartphones. Oxygen levels in the blood will be measured by a thumbprint scan, pupil dilation by the camera, and breathing rate, acoustics and volume via a microphone.
This data will then be uploaded and fed into the machine learning model to create a possibility: is the user a potential candidate for self-isolation and / or definitive medical testing? There is no timeline for the availability of the app, but anyone can download the Caredemic app on a smartphone. Cardamic is stressful in place of medical testing.
The application will provide a valuable supplement to aid early detection of COVID-19 — even in the case of mild or asymptomatic infections — within true versus false positives. In symptomatic cases, the device can generate better precision and more useful data than most medical personnel can achieve with a simple visual assessment.
The company says the app works using its extensive data collection list based on the complexity of predicting early signs of the disease. Therefore, there is a need for different machine learning and data analysis teams around the world to effectively deal with different algorithms for different insights. "Based on the key data collected, each team will be able to create a" derivative "that is either a view of data or metadata.
Within the same machine learning team or different teams, depending on each other We can chain derivatives. That's why we need at least 10 machine learning volunteer teams around the world. We are actively looking for machine learning experts to help us.
The prize is also attached as an additional incentive to participate in it. The company says that when it comes to finding data correlations, the expertise required for it is technical rather than medical. "We need algorithms There is a need for positivity confirmed by. For example, the 'acoustic signature' of pneumonia is more a biotechnological question than a therapy The website has a list of references that can be found here.
Company to contribute baseline data for the initial machine learning phase of the project, both for the infected and healthy (16 years or older) Plans to launch a global call for volunteers. In a completely anonymous process, participants will complete a brief survey, and then carry out a cardiovascular series of measurements.
The company states that more than 10,000 volunteers will be needed to contribute to the data to make the cardiomic effective. Questions and data collection points can be seen here. To ensure data privacy, the company says it will not collect volunteers' names or GPS locations, phone's IP addresses, serial numbers, or operating system IDs, and the information will only be used for the development of this app.
An Alberta-based tech company is reaching out with universities and machine learning experts from around the world to contribute to its cardiovascular project, an app that serves as an earlier screening process for the ongoing epidemic.
The application has received contributions from Western Economic Diversification Canada, Kinkaid Enterprises Inc., Universe Machine Corporation and several anonymous donors. To bring the project to the ground, Chief Executive Officer of Pleasant Solutions Thomas Stachura told IT World Canada in an email.
Apart from Pleasant Solutions, Caredemic, a software developer, has several projects under its belt, including the Paranoid project, which aims to deactivate the stinging ears of smart homes. “This is a company that has been around for a dozen years, and whose software NASA trusts to manage employee passwords.
So what us The Department of Energy then staffs at Buckingham Palace. We have recently developed a line of digital privacy devices and launched earlier this year. We have an extensive history in the tech industry, with much of our business in the B2B sector, ”Stakura wrote in the email.
With Karademic, the screening process will measure a user's various data points, including their oxygen level, pupil dilatation, breathing rate, acoustics, and volume, which are built into most smartphones. Oxygen levels in the blood will be measured by a thumbprint scan, pupil dilation by the camera, and breathing rate, acoustics and volume via a microphone.
This data will then be uploaded and fed into the machine learning model to create a possibility: is the user a potential candidate for self-isolation and / or definitive medical testing? There is no timeline for the availability of the app, but anyone can download the Caredemic app on a smartphone. Cardamic is stressful in place of medical testing.
The application will provide a valuable supplement to aid early detection of COVID-19 — even in the case of mild or asymptomatic infections — within true versus false positives. In symptomatic cases, the device can generate better precision and more useful data than most medical personnel can achieve with a simple visual assessment.
The company says the app works using its extensive data collection list based on the complexity of predicting early signs of the disease. Therefore, there is a need for different machine learning and data analysis teams around the world to effectively deal with different algorithms for different insights. "Based on the key data collected, each team will be able to create a" derivative "that is either a view of data or metadata.
Within the same machine learning team or different teams, depending on each other We can chain derivatives. That's why we need at least 10 machine learning volunteer teams around the world. We are actively looking for machine learning experts to help us.
The prize is also attached as an additional incentive to participate in it. The company says that when it comes to finding data correlations, the expertise required for it is technical rather than medical. "We need algorithms There is a need for positivity confirmed by. For example, the 'acoustic signature' of pneumonia is more a biotechnological question than a therapy The website has a list of references that can be found here.
Company to contribute baseline data for the initial machine learning phase of the project, both for the infected and healthy (16 years or older) Plans to launch a global call for volunteers. In a completely anonymous process, participants will complete a brief survey, and then carry out a cardiovascular series of measurements.
The company states that more than 10,000 volunteers will be needed to contribute to the data to make the cardiomic effective. Questions and data collection points can be seen here. To ensure data privacy, the company says it will not collect volunteers' names or GPS locations, phone's IP addresses, serial numbers, or operating system IDs, and the information will only be used for the development of this app.
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