Health IT: Healthcare Analytics

Data in today's healthcare model is already enormous, and growing every day. From medical records to genomics, providers and payers can garner new insights across a spectrum of applications ranging from better personalized individual care to predictive models for large population cohorts, resulting in better patient outcomes with improved provider and payer resource utilization.

Healthcare Analytics Related Material

Healthcare organizations are optimizing infrastructure to improve efficiency and reduce cost

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Brief: See how predictive clinical analytics based on Intel® architecture help healthcare providers get a more complete picture of patient health.

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Next-generation sequencing (NGS) creates transformative opportunities to expand our understanding of biomedicine, reshape clinical care, and improve human health.

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White Paper: The Irys* System from BioNano Genomics delivers the throughput for optical next-generation mapping with the Intel® Xeon Phi™ coprocessor.

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With the right analytics infrastructure, organizations can improve population health and lower costs by tapping biometric data sources.

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Thanks to advances in remote patient monitoring technology, healthcare providers have unprecedented opportunities to improve patient outcomes while reducing costs when managing post-acute and chronic conditions.

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Paper explores Intel's ethnographic research on scaling genomics precision medicine for cancer care in the PRC and the US, which promises new approaches to diagnosing, treating, and preventing cancer and other diseases.

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Explore this solution brief and discover how Intel's reference architecture for genomics clusters designed using Intel® Scalable System Framework can dramatically reduce genome sequencing time as well as significantly reduce total cost of ownership for genomics clusters.

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White Paper: See how UNICANCER is using next-gen big data analysis to improve clinical trials, health economics, and researcher productivity.

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The Living Heart Project extends the value of the high-performance computing in the life sciences, alongside research and therapies in areas such as genomics, pharmacology, and computational biology.

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Using SAP Foundation for Health, built on SAP HANA*, organizations can combine traditional data sources and vital patient data—clinical, research, personal medical, social information, and more for in-depth health analytics.

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Big Cloud Analytics and Intel have partnered to deliver a solution for addressing quality-of-life and cost-of-care issues with Intel® powered wearable fitness trackers and the COVALENCE* Health Analytics Platform.

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Sustained innovation in extreme-scale computing will help usher in a transformative era of personalized biomedicine.

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The Trusted Analytics Platform provides a predictive solution that helps doctors at Penn Medicine improve treatment and patient heart health.

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This paper shows how one healthcare institution—Penn Medicine—is using big data solutions to derive new insights and improve patient care.

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Icahn School of Medicine at Mount Sinai has been working with Intel to use Trusted Analytics Platform to apply data science, graph analytics, and machine learning for faster discovery of new drug therapies.

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The St. John's Sepsis Agent* monitors vital data in real time to predict with a high level of accuracy whether a patient will develop sepsis.

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The Translational Genomics Research Institute develops early diagnostics to improve the lives of people like Shelby through molecular medicine.

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Apixio's blend of healthcare analytics and cognitive computing helps payers and providers achieve practical insights and bottom-line benefits from existing data.

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Smithsonian Institute for Biodiversity Genomics halves genome assembly time using Intel® Xeon® processor E7 v3 family and Intel® Solid State Drives.

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Breakthroughs in analyzing unstructured clinical data show potential to improve the delivery of integrated, resource-efficient patient care.

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Read about research efforts around next-generation sequencing (NGS) technologies that generate vast amounts of variant data, posing a big computational challenge.

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Explore this white paper and discover how in this Genome-wide association study (GWAS), Intel Reference Architecture can be used to efficiently perform analysis on big genome sequencing datasets, like Wellderly and 1000 Genomes.

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OHSU Director of Cancer Research Brian Druker and other doctors discuss OHSU’s collaboration with Intel to create computer architectures optimized for sequencing cancer genomes and personalizing cancer care.

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Today, making use of big data is becoming mainstream in various industries and business sectors. The healthcare industry is no exception. In particular, medical facilities, which generate and process huge volumes of medical information and medical device data, have been accelerating big data utilization.

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White Paper: See how Intel is working with GE to deliver Predix*, a computing platform that uses big data analytics to improve the quality and efficiency of healthcare through application integration and by sharing and analyzing complex data sets.

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Intel and Cloudera Use Predictive Analytics to Help a Large Hospital Group Reduce Readmission Rates.

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The increasing digitization of healthcare information is opening new possibilities for providers and payers to enhance the quality of care, improve healthcare outcomes, and reduce costs. Technology advances, regulatory mandates, and government incentives have accelerated the move from paper to digital health records.

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With nearly USD 450 million annually in research expenditures, Arizona State University is a research leader. ASU partnered with Dell to create the NGCC, ASU's Next Generation Cyber Capability to advance big data and high-performance computing research in complex adaptive systems.

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Life sciences benefit from big data analytics enabling personalized medicine for high-quality care, and better outcomes. Some management challenges the life sciences face are data security and proper analytics for using data in and efficient and expeditious manner.

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