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Bio digital twins and the future of health innovation

CIO Business Intelligence

Essentially, the technology involves the replication of the human body in software models. Using these models, healthcare providers can test drugs and therapies with unprecedented speed and accuracy, reducing risks for both patients and physicians.

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

Then artificial intelligence advances became more widely used, which made it possible to include optimization and informatics in analysis methods. Machine learning. Computers learn to act on their own, we no longer need to write detailed instructions to complete certain tasks. Where to Use Data Science?

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Build efficient, cross-Regional, I/O-intensive workloads with Dask on AWS

AWS Big Data

After deployment, the user will have access to a Jupyter notebook, where they can interact with two datasets from ASDI on AWS: Coupled Model Intercomparison Project 6 (CMIP6) and ECMWF ERA5 Reanalysis. He and his team explore new ways the Met Office can provide value through product innovation and strategic partnerships.

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Achieve competitive advantage in precision medicine with IBM and Amazon Omics

IBM Big Data Hub

Processing terabytes or even petabytes of increasing complex omics data generated by NGS platforms has necessitated development of omics informatics. Most individual omics informatics tools and algorithms focus on solving a specific problem, which is usually part of a large project. clinical) using a range of machine learning models.

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How Zurich Insurance Group built a log management solution on AWS

AWS Big Data

The new approach would need to offer the flexibility to integrate new technologies such as machine learning (ML), scalability to handle long-term retention at forecasted growth levels, and provide options for cost optimization. Eventually, this data could be used to train ML models to support better anomaly detection.

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How SafeGraph built a reliable, efficient, and user-friendly Apache Spark platform with Amazon EMR on Amazon EKS

AWS Big Data

These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. He’s passionate about building with serverless technologies, machine learning, and accelerating his AWS customers’ business success. Their costs were climbing.

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Innocens BV leverages IBM Technology to Develop an AI Solution to help detect potential sepsis events in high-risk newborns

IBM Big Data Hub

We joined forces with a Bio-informatics research group from the University of Antwerp and started taking the first steps in developing a solution. The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions.

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