Data Science fighting with deadly Covid-19
The deadly novel coronavirus is not an unknown subject anymore. On January 28, WHO announces, and that time world was suffering to tackle covid-19. This is where technologies such as Artificial Intelligence (AI) and Machine Learning (ML) come into play. Analytics have transmuted the way disease outbreaks are tracked and managed, hence preserving lives.
Screening patients and diagnosing Covid-19
When an incipient pandemic hit, diagnosing individuals is arduous. Testing on a large scale is arduous and tests are liable to be sumptuous, especially in the commencement. Anyone who has any symptoms of COVID-19 is liable to be solicitous that they have contracted the disease, even if the same symptoms are indicative of many other, potentially milder diseases additionally.
When it comes to utilizing machine learning to avail diagnose COVID-19, promising research areas include:
- Utilizing face scans to identify symptoms, such as whether the patient has a fever
- Utilizing wearable technology such as perspicacious watches to probe for tell-tale patterns in a patient’s reposing heart rate,
- Utilizing machine learning-powered chatbots to screen patients predicated on self-reported symptoms.
Contact tracking and Quarantine enforcement
The Chinese government rolled out a “Close Contact Detector” App that alerted users if they were in contact with someone who had the virus. Homogeneous App was utilized by many countries like (Singapore: Trace Together, India: Aarogya Setu). As countries search for ways to exit lockdown and eschew or manage a second wave of COVID-19 cases, many have turned to the promise held by contact-tracing apps. Though there is a privacy concern, this tracing technology, together with AI-driven prognostication from data accumulated from these apps (proximity, duration of contact, etc.)
Speeding up drug development
Artificial Intelligence & Machine learning can expedite the drug development process significantly without sacrificing quality control. When researchers were endeavoring to find minute molecule inhibitors of the Ebola virus, they discovered that training Bayesian ML models with viral pseudotype ingression assay and the Ebola virus replication assay data availed expedite the scoring process. This expedited process expeditiously identified three potential molecules for testing.
Predicting the spread of infectious disease using social networks
Facebook is working with researchers at Harvard University's School of Public Health and the National Tsing Hua University, in Taiwan, sharing anonymized data about people's movement and high-resolution population density maps, which avail them forecast the spread of the virus. YouTube is utilizing its homepage to direct users to the World Health Organization and other groups, for education and information, while working to abstract videos suggesting alternative remedies as soon as they go live.
Artificial Intelligence & Machine learning is a paramount implement in fighting the current pandemic. If we take this opportunity to accumulate data, pool our erudition, and coalesce our skills, we can preserve many lives – both now and in the future.
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