Applications of Data Science in Medical Devices
Scott Plewes | October 10, 2019
As more medical device vendors look to create data-driven products and demonstrate improved patient outcomes, an understanding of the role data science plays and how it can be integrated into the product development process will be key to their success.
The data collected (or potentially collected) by medical devices presents a plethora of opportunities to be leveraged to demonstrate outcomes or create new data-enabled products. However, with these opportunities comes the challenge of integrating data science into existing product development practices.
In this guide, we demystify the domain of data science and articulate what’s actually involved, dive into the two main approaches to applying data science that medical device vendors can use to leverage their data and, lastly, review the most common pitfalls experienced by teams that lead to failed data science initiatives as well as how to avoid them.
You’ll walk away with:
- A breakdown of the 4 components of a data science project
- Two frameworks for leveraging medical device data
- 5 pitfalls we commonly see that cause projects to miss expectations
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