Better Patient Outcomes Using Ayasdi Machine Intelligence
Ayasdi’s Machine Intelligence software solves the most complex and impactful analytical challenges for healthcare organizations in both the provider and payer space. Ayasdi has revealed genetic traits of cancer survivors with the Netherlands Cancer Institute; discovered six distinct subtypes of Type II Diabetes patients with Mount Sinai School of Medicine; and made significant advancements in improving patient outcomes with Mercy – resulting in an anticipated savings of more than $100M for the hospital by changing the way it develops and deploys clinical pathways.
“Mercy, the fifth largest Catholic health care system in the U.S., and a ‘Most Wired’ health care organization, is a recognized leader in applying innovative technologies to produce break-through patient outcomes and superior ROI,” said Vance Moore, Senior Vice President Operations at Mercy. “Using our vast repositories of clinical and patient data, we see Ayasdi’s capabilities as a critical element to reduce costly clinical variations and improve our operational best practices, leading us to harvest millions of dollars in unnecessary expenses, all while improving the lives and welfare of our patients.”
“Ayasdi aims to make complex data useful for healthcare providers and payers through Machine Intelligence, which represents the next generation of healthcare data analytics,” said Gurjeet Singh, CEO of Ayasdi. “With Ayasdi, healthcare providers can examine millions of patient cases and rapidly ascertain pathways that deliver the highest quality of care, in the most cost-effective manner.”
“Rapidly defining and refining optimal clinical pathways is just one example of what healthcare providers can accomplish with Ayasdi,” said Johan Grahnen, Lead Data Scientist Healthcare of Ayasdi. “Our platform also helps clinicians and operations teams accurately assess readmission risk, evaluate the comparative effectiveness of drugs and devices, and implement population management.”
Today’s time-consuming, iterative approach to data analysis relies upon specialized experts to ask the right questions and oftentimes write code. By contrast, Ayasdi’s Machine Intelligence software employs a data-driven approach that thoroughly inspects the entire dataset to find the most important patterns, values and anomalies. It accelerates the discovery process, and improves the quality of the analysis, empowering domain experts and data scientists to apply these insights more efficiently and effectively.
Ayasdi is transforming how the world uses data to solve complex problems. Founded in 2008 after a decade of research at Stanford, DARPA, and NSF, Ayasdi is pioneering a new approach for enterprises to automatically discover and operationalize insights from their data. Ayasdi’s Insight Discovery platform uses Topological Data Analysis (TDA) combined with an ensemble of machine learning techniques to enable data scientists, domain experts, and business people to achieve value from their data without the need to write code, queries, or ask questions.
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