Improved care and better, more efficient practices
As healthcare becomes a bigger and bigger part of the national and world economy, competitive and price pressures are mounting. At the same time, customers are more demanding of their experience as patients, both before, during, and after treatment. Add to that dizzying regulatory uncertainties, and healthcare companies – both providers and insurers – are facing significant challenges. Data science can help healthcare companies keep abreast of these changes by helping to ensure optimal care experiences for patients and efficient operations behind-the-scenes.
Get every person the best possible treatment. Better yet, take steps to prevent health issues from arising in the first place.
Discover new treatments
Find new ways to treat disease and other health issues, including identifying which treatments are best for which specific patient types.
Optimize asset utilization
Ensure everything from rooms to bed to equipment to people is utilized optimally. Balance maximizing revenue and ensuring no one gets turned away for care.
Healthcare Use Cases
“Machine learning allowed this US state auditor to integrate and consider various data sources, create meaningful features and scores, provide context and explanations, and detect networks of fraudsters.”
“The fusion of RapidMiner and Tableau allows us to go from an anecdotal approach to a data-supported approach that enables us to create more meaningful interventions and better patient care moving forward.”
Lightning Fast Data Science
Built for analytics teams, RapidMiner unifies the entire data science lifecycle from data prep to machine learning to predictive model deployment. Organizations can build machine learning models and put them into production faster than ever, using RapidMiner’s lightning fast visual workflow designer and automated modeling capabilities. 400,000 analytics professionals use RapidMiner products to drive revenue, reduce costs, and avoid risks.