[{"innerBlocks":[],"name":"core\/freeform","postId":2739,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"The University of Maryland\u2019s Center for Health Information and Decision Systems is entering a collaborative agreement with a vendor to expand efforts to develop applications of machine learning and neural network solutions.
The center will work with Inovalon, a Bowie, Md.-based company that operates a cloud-based platform that enables the use of predictive analytic components for research.

Under the agreement, the center will join Inovalon\u2019s ongoing development initiative focused on natural language processing, machine learning and deep learning solutions utilized within the Inovalon ONE Platform.

Use of these technologies, as well as the large-scale computing environments available on its ONE Platform, Inovalon has been researching high-speed analysis of unstructured data contained within raw clinical documentation, such as that found within electronic health record systems. The company\u2019s dataset has data pertaining to 231 million patients and 34 billion medical events.

The university\u2019s Center for Health Information and Decision Systems (CHIDS) is an academic research center in the Robert H. Smith School of Business; it works in collaboration with industry, clinical and government partners to develop solutions to the challenges surrounding the design, adoption and integration of information technologies into the healthcare system.

Also See:<\/b> IBM taps machine learning to predict cirrhosis mortality rates<\/a>

The center\u2019s research seeks to understand how digital technologies can be more effectively deployed to address outcomes such as patient safety, healthcare quality, efficiency in healthcare delivery and reduction of health disparities.

\u201cWe are at a tipping point for harnessing diverse data sources and utilizing advanced artificial intelligence capabilities to transform healthcare in ways we had not imagined in the past,\u201d said Ritu Agarwal, participating researcher and the Robert H. Smith School\u2019s senior associate dean for research.

\u201cWe are very pleased to be collaborating with UMD\u2019s CHIDS, pioneers in the study of digitally enabled health system transformation and known for its thought leadership and research collaborations,\u201d said Eric Sullivan, senior vice president, innovation and data strategies at Inovalon.","saveContent":"The University of Maryland\u2019s Center for Health Information and Decision Systems is entering a collaborative agreement with a vendor to expand efforts to develop applications of machine learning and neural network solutions.
The center will work with Inovalon, a Bowie, Md.-based company that operates a cloud-based platform that enables the use of predictive analytic components for research.

Under the agreement, the center will join Inovalon\u2019s ongoing development initiative focused on natural language processing, machine learning and deep learning solutions utilized within the Inovalon ONE Platform.

Use of these technologies, as well as the large-scale computing environments available on its ONE Platform, Inovalon has been researching high-speed analysis of unstructured data contained within raw clinical documentation, such as that found within electronic health record systems. The company\u2019s dataset has data pertaining to 231 million patients and 34 billion medical events.

The university\u2019s Center for Health Information and Decision Systems (CHIDS) is an academic research center in the Robert H. Smith School of Business; it works in collaboration with industry, clinical and government partners to develop solutions to the challenges surrounding the design, adoption and integration of information technologies into the healthcare system.

Also See:<\/b> IBM taps machine learning to predict cirrhosis mortality rates<\/a>

The center\u2019s research seeks to understand how digital technologies can be more effectively deployed to address outcomes such as patient safety, healthcare quality, efficiency in healthcare delivery and reduction of health disparities.

\u201cWe are at a tipping point for harnessing diverse data sources and utilizing advanced artificial intelligence capabilities to transform healthcare in ways we had not imagined in the past,\u201d said Ritu Agarwal, participating researcher and the Robert H. Smith School\u2019s senior associate dean for research.

\u201cWe are very pleased to be collaborating with UMD\u2019s CHIDS, pioneers in the study of digitally enabled health system transformation and known for its thought leadership and research collaborations,\u201d said Eric Sullivan, senior vice president, innovation and data strategies at Inovalon.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

University of Maryland to study advanced computing in healthcare

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