Fitness and Digital Health

Diagnosing and Treating Machine Learning Models Afflicted by COVID-19

COVID-19 has disrupted the lives of a huge number of individuals and influenced organizations all over the world. Its effect has been especially huge on many machine learning (ML) models that organizations use to anticipate human conduct. 

Organizations need to make moves to profoundly look at ML models and gain the experiences expected to viably refresh models and encompass business rules.

Read the article below to know more about it: 

COVID-19 has disrupted the lives of millions of people and affected businesses across the world. Its impact has been particularly significant on many machine learning (ML) models that companies use to predict human behavior. To know more, Click here 

Also Read: Harness digital tech for inclusive healthcare


COVID 19 Impact On Machine Learning Models

A lot of business procedures are working with the assistance of data science implementations, i.e. machine learning models, time series models, and AI solutions. These models take into appreciation the historical data as well as past directions. In the Pre-COVID area, all models were working well with the changing climate.

As the consequences of COVID-19  the impact on social and economic behaviors. Updates to business rules and models will need to be done in sync with overall behavior changes in each of the stages. Companies need to adopt a strategy of measure-understand-act and to constantly assess, examine and adjust ML models in production or improvement and surrounding business rules.

Read the articles below to know more about it:

COVID 19 Impact On Machine Learning Models

A lot of business processes are functioning with the help of data science implementations, i.e. machine learning models, time series models, AI solutions etc. To read more, Click here 

How the COVID-19 Pandemic Affects Machine Learning in Business

COVID-19 has disrupted every single social, economic and political aspect of life and it’s difficult to predict how the crisis derived from the pandemic will evolve. To know more, Click here 

Machine Learning Models Estimate Seasonal Impact of COVID-19

Researchers will apply machine learning algorithms to environmental data to determine whether COVID-19 surges and wanes in different seasons. To read more about it, Click here  

Machine learning model to project the impact of COVID-19 on US motor gasoline demand

Owing to the global lockdowns that resulted from the COVID-19 pandemic, fuel demand plummeted and the price of oil futures went negative in April 2020. To find more info,  Click here 



How to Diagnose ML Models Affected by COVID? 

Examining how machine learning models have been affected means going through a practice to both measure and understand how the models behaved previous to the coronavirus, how they are behaving now, why they are behaving differently and then to determine if the new behaviour is anticipated and accurate, or is no longer reasonable.

Models need to be additionally adaptive and able to leverage business techniques in the best possible way. Models will become outdated if not modified. There will have to be mechanisms in place for following the trends and the omissions in model value predictions. Data Science requires to quickly adapt to the fast stepped changes that are occurring in the world due to the pandemic.

Read the articles below to know more about it: 

How to make AI/Machine Learning models resilient during COVID-19 crisis

COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. To read more, Click here 

3 ways COVID-19 is transforming advanced analytics and AI

While the impact of AI on COVID-19 has been widely reported in the press, the impact of COVID-19 on AI has not received much attention. To continue to read more, Click here 


Also Read: Smart needles pioneering revolution in cancer diagnosis and treatment


COVID-19-driven concept shift has built concern over the usage of machine learning to continue to run business value following cases of false outputs and misleading results from a variation of fields.


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