Rapid AI Insights: Edition 15

Hello,

Welcome to a new edition of Rapid AI Insights. This week, we look into how #AI can help alleviate the burdens placed on #healthcare workers and the system, and understand how to evaluate #appliedAI companies amidst the hype. In ML 101, we look into the concepts of #overfitting and #underfitting.

Using AI to address the healthcare crisis

There have been a recurring number of violent incidents targeting healthcare workers, and this is one of many issues that continue to plague the healthcare system in a country like the US. Poor working conditions take a toll on their physical and mental well-being, leaving them exhausted and susceptible to burnout.

AI, if leveraged responsibly, can ease some of this burden:?

• Reduce violence from patients: Predicting potential aggression by assessing patient histories, behavioral patterns and contextual factors, enabling early intervention
• Reduce violence from visitors:? AI-powered security systems can create safer environments using advanced sensors, cameras and machine learning models?
• Preventing burnout due to administrative tasks: Using AI in EHR (Electronic health record) management to view clinical data real time from medical devices and records.
• Manage liability due to misdiagnosis: AI can aid more accurate diagnosis, by identifying potential health concerns and aiding doctors in their diagnosis process.?

What to look for in applied AI companies?

AI has moved from being a theoretical construct to a very real technology being used in millions of ways. Applied AI brings AI out of the lab and deploys it to work with real-world use cases and show positive results.?

The market not only for solutions but for investments is active and Mckinsey identified key six findings for stakeholders, including investors, to keep in mind as they think about companies in the industry.?

• A clear ROI story
• Better customer segmentation models
• A plan for multipersona marketing
• Captive workflows to defend against competition
• New efficiency levers
• A multiyear go-to-market road map

These also serve as valuable litmus tests to identify a truly promising AI company amidst the hype, for purposes beyond investment, such as employment opportunities, and making purchases of AI tools and solutions, to name a few.?

Machine Learning 101: Overfitting and underfitting?

This week, we continue with concepts relating to ML model performance. When a machine learning model is not performing as expected, two things to check for are overfitting and underfitting.?

Overfitting is when a model performs very well for training data but has poor performance with test data i.e. new data. In some cases, when a model gets trained with a large volume of data, it starts learning from the noise and inaccurate data entries in the data.

Underfitting is when the model has not learned the patterns in the training data well and is unable to generalize well using new data i.e the model is too simple to capture data complexities.??

Both of these can be tackled by making appropriate changes to the dataset as well as the model, depending on the source of the issue. Here’s a guide to learn more.?

About RapidCanvas

RapidCanvas is a no-code AI platform for business users to go from idea to live enterprise AI solution within hours, reducing time to value by over 90%, when compared to traditional AI build-and-deploy processes. RapidCanvas creates out-of-the-box AI solutions tailored to your needs using our proprietary AutoAI technology. Our data science experts work with you to optimize the results to your satisfaction; we combine the efficiency of algorithms with the experience of human experts. RapidCanvas work with leaders in financial services, retail, renewable energy, and manufacturing.?