Can Docs Use Machine Learning to Determine COVID Treatment Course?
COVID-19 is in the news less and less these days. With luck it will soon be a thing of the past – scientists are using remarkable new techniques and technology to vanquish its threat. The COVID treatment course is about to be supercharged, and it’s all thanks to the exponential processing power of machine learning.
As reported by Health IT Analytics, doctors are learning to harness machine learning to better help COVID patients. A new study found that a new approach can trace patient responses to drugs!
Using data from a Chinese hospital, the University of California, Riverside’s researchers found that automated, machine learning analysis could assess patient age, weight and other illnesses to identify the ideal drug combinations for lessening COVID-19 recurrence.
COVID treatment course boost
Way back at the beginning of the pandemic, doctors prescribed drugs to patients with the disease – in America, treatment was limited to just a handful of drugs. In China, however, the selection pool was much bigger, consisting of eight different options. We’re so used to being prescribed a proven medicine that the anecdotal lockdown living – “Are you an AstraZeneca or Pfizer?” – really did feel novel. Countries pooled research and resources together, yes, but each nation ultimately had to deal with the pandemic separately.
The Centres for Disease Control and Prevention indicated that in 2021, COVID-19 was the third leading cause of death in the US, as opposed to Shenzhen, China, where death rates were not as common. UCR researchers noted that COVID patients in China would quarantine in government-run hotels following their hospital release. Attention was paid to whether demographics influenced the potency of certain drug combinations – at the time, citizens engaged in rampant speculation. Thanks to the University of California, Riverside, we might have some concrete answers.
“Researchers also had to dedicate a level of attention to how variations in distribution, or lack thereof, may have affected outcomes. If mostly obese people used a particular combination of drugs that failed, researchers would not have sufficient evidence to blame the selection or weight.”
– Mark Melchionna, HealthITAnalytics
A richer picture
Jiayu Liao, the associate professor of bioengineering and study co-author, had this to say: “When we get treatment for diseases, many doctors tend to offer one solution for people 18 and up. We should now reconsider age differences and other disease conditions, such as diabetes and obesity.”
It’s clear that such extensive research is critical for future COVID sufferers, and should a similar event happen again. By factoring in an extensive range of variables for each patient and utilising tailored machine-learning protocols to cut down on deduction, Liao and his team were able to negate some of our nagging questions about the pandemic.
If the worse does happen again, thanks to this work, the lingering effects may be that much easier to treat. What do you think we could stand to learn from COVID-19? Sound off in the comments!
For more on how the NHS tackles COVID-19 today, head here.
Source: Can Docs Use Machine Learning to Determine COVID Treatment Course?
Want to know more about how medicine can affect you, personally? Read MHRA and Genomics England to Launch Revolutionary ‘Biobank’ for Personalised Medicine.
