Growth Experiments is a complete platform to track ideas, hypotheses and results.
The radiology department of an average healthcare facility is likely searching for improvements. Even before COVID-19, 45% of radiologists experienced burnout at one point in their career. They felt overwhelmed with the administrative burden and the large number of images they had to check manually, which could reach up to a hundred scans per day. Additionally, radiology practice is lacking non-invasive methods for tissue classification. Invasive procedures take time and cause stress to patients. Luckily, AI healthcare solutions are coming to the rescue. The global AI radiology market was valued at $21.5 million in 2018, and it is forecast to reach $181.1 million in 2025, growing at a staggering CAGR of 35.9%. However, despite the numerous advantages of AI in radiology, there are still challenges preventing its wide deployment. How to properly train machine learning to aid radiology? Where does AI stand when it comes to ethics and regulations? How to make a strong business case for investing in artificial intelligence in radiology?
Web scraping (data search and extraction from HTML-pages) has become a real gem for digital marketers and analysts that need to collect massive data sets for further research. This blog post contains 75 real-life scraping cases and a cheat sheet with regexp for the most popular sites like Google, Amazon, Facebook, etc.
Data science is the field of applying advanced mathematical and statistical techniques to large sets of data to uncover insights that can improve the performance of different parts of a business. Data science is used in growth to uncover commonalities between types of users that are either successful or unsuccessful with a product. Marketers and growth teams use data science findings to improve the performance of their product, user acquisition funnel, user retention and more. These are the best articles on how to use data science to grow your business. From how to analyze data using R, pandas for Python, regression, model building, SQL and more, you'll learn how to apply data science concepts to growth.