Large-scale Distributed, Cognitive Computing in Healthcare

Analytics and machine learning can enhance the electronic information provided to doctors. We need to provide clinicians with more information so they can make better decisions about patient diagnoses and treatment options, at the same time understand the possible outcomes and cost for each one. The value of machine learning in healthcare is its ability to process huge data sets beyond the scope of human capability, and then reliably convert analysis of that data into clinical insights that aid physicians in planning and providing care, ultimately leading to better outcomes, lower costs of care, and increased patient satisfaction. As more data is available, we can give more information to patients. At Owned Outcomes, we use our proprietary softwares to analyze data, train data using model agnostic ML algorithms, and compare data to provide information to providers and patients.