Drive better patient outcomes with predictive analytics

Healthcare providers are increasingly capturing and analyzing data from bedside sensors, bio-monitors, HL7, FHIR, and other streaming and IoT-scale data feeds. Environmental and epigenetic factors such as ambient light, ambient noise, stress, and clinical interventions represent examples of enriching healthcare predictive analytics data. Cloudera provides a scalable next-generation, hybrid data management platform that empowers physicians, researchers, and others to easily collect, process, secure, and analyze all of this data for evaluating ways to impact patient outcomes.

Analysis of the relevant DNA sequences, whether whole genome, exome, methylation or multi-omics, puts us in reach of precision medicine and high confidence biomarker  discovery for the first time. Cloudera’s enterprise-grade platform can drive tremendous improvements in cost and in computing power over traditional compute approaches in tertiary or downstream molecular analytics at scale. This helps enable use cases from health system pathology departments performing pharmacogenomics to research labs doing genome-wide association studies. Cloudera enables the fastest path to merge omic data with clinical/phenotype data from any technology in the market. More than  a dozen organizations have selected Cloudera as their precision medicine repository or enterprise variant store for unlimited scale.

From enabling NLP and predicting sepsis, to developing algorithms that help identify cancerous tumors, machine learning is poised to fundamentally transform the healthcare and pharmaceutical space.

And Cloudera provides the next generation, open, hybrid data management platform that enables organizations to ingest, store, process, and analyze vast amounts of data that is essential in building machine learning models. Cloudera Data Science Workbench helps accelerate data science at scale to build, test, iterate, and deploy machine learning models in production using by taking advantage of massively parallel compute and expanded data streams.

Use cases for NLP in Healthcare

IoT is undoubtedly transforming the healthcare industry today enabling use cases such as remote patient monitoring, telemedicine, and chronic disease management. 

Cloudera supported technologies, including Cloudera DataFlow provides a real-time streaming analytics platform that can help  providers easily capture, combine, secure, and drive analytics on data feeds from bedside sensors, bio-monitors and other connected healthcare IoT devices, at scale. Data from IoT sensors can then be stored, analyzed, and used to build machine learning models to predict patient outcomes and the next best course of action.

As the healthcare industry adopts more technology, especially the digitization of health records, it is imperative that cybersecurity stays at the forefront of all the data management projects. Cloudera empowers you to proactively secure healthcare data by accelerating threat detection as well as investigation and response, through machine learning and complete enterprise visibility.

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