Ways Machine Learning is helping us fight the viral pandemic and why it is important to learn ML right now
- Identify who is most at risk.
- Diagnosing patients,
- Develop medications faster
- Find existing medications that can help
- Predict the spread of the disease,
- Better understand viruses,
- Map of where the viruses come from, and
- Predict the next pandemic.
To say the least, machine learning is an important tool to combat the current pandemic. By taking advantage of this opportunity to collect data, pool our knowledge and combine our skills, we can save many lives, both now and in the future. You can be part of this revolution by learning ML at upGrad and training yourself to do things that interest you.
Here are a few ways machine learning is proving invaluable in predicting risks in many areas:
- Machine learning can help predict three types of medical risks: infection, severity, and outcome. While it is still too early for specific COVID-19 research, the first results look promising.
- By predicting the risk of infection, machine learning has helped determine risk factors such as age, pre-existing conditions, general hygiene habits, social habits, etc. In particular, Dave DeCaprio and others have used machine learning to create an Initial Vulnerability Index for COVID-19. Prevention measures, such as wearing masks, handwashing, and social distancing, are also likely to influence overall risk.
- To help diagnose COVID-19, machine learning is taking action to use facial scanners to identify symptoms. It is also integrated with portable technology, such as smart watches to look for telltale patterns in a patient’s resting heart rate, and chatbots with machine learning technology can detect patients based on self-reported symptoms.
- This new pandemic needs the medical world to accelerate drug development, rapidly introduce a vaccine, and a reliable diagnostic method. The current methods used involve a lot of trial and error, making them extremely slow. While it may take months to isolate even a viable candidate vaccine, machine learning can speed up this process essentially without compromising quality control.
- Not just new drugs, the problem also requires identifying effective existing drugs. Machine learning can also help here. Medical professionals can prioritize drug candidates much faster by automatically developing knowledge charts and predicting interactions between drugs and viral proteins.
There are many more ways that machine learning can help the world combat this pandemic and solve many other problems. However, there is only one way you can be part of this advancement: by earning a
Master in Machine Learning through a coveted educational platform like upGrad. They offer the only online M.Sc in ML & AI for professionals who work with more than 450 hours of learning through more than 30 case studies and tasks. You’ll also earn over 5 hands-on Capstone hands-on projects for over 25 industry mentoring sessions. Your questions will receive timely resolution, thanks to dedicated student success mentors.
This is your chance to be the hero this world needs by studying Machine Learning.
To top it off, the Master of Science in Machine Learning & AI at upGrad costs 1/10 of the cost of the offline title. UpGrad students have received an average salary increase of 58% after successfully completing the program. The highest salary package that upGrad students have achieved is INR 72 lakhs per year. Top-performing students will get a paid opportunity from all participants to attend the ES conference in the UK, along with global recognition and networking with a strong student base.
If you have decided to add this extraordinary update to your skill set, you may be one of the over 12,600 students trained by upGrad. Your 18-month program can be completed by dedicating 15 hours per week and the next batch begins on May 4, 2020. You can also take advantage of the “No EMI cost” option in the program fee. Enroll now to start learning.
Get IIIT Bangalore and LJMU Dual Student Status upon successful completion of the program!
Disclaimer: This article was produced on behalf of upGrad by the Times Internet Spotlight team.