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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

With predictive analytics, organizations can find and exploit patterns contained within data in order to detect risks and opportunities. Models can be designed, for instance, to discover relationships between various behavior factors. Financial services: Develop credit risk models.

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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

At Innocens BV, the belief is that earlier identification of sepsis-related events in newborns is possible, especially given the vast amount of data points collected from the moment a baby is born. Years’ worth of aggregated data in the NICU could help lead us to a solution.

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Research shows extensive use of AI contains data breaches faster and saves significant costs

IBM Big Data Hub

Under-deployed tools and solutions that do the minimal that’s “good enough” or that face other barriers like the risk aversion to fully automating processes that could have unintended consequences. Budget constraints for cybersecurity and perception that their organization is sufficiently protected.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis.

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The most valuable AI use cases for business

IBM Big Data Hub

Automotive With applications of AI, automotive manufacturers are able to more effectively predict and adjust production to respond to changes in supply and demand. They can streamline workflows to increase efficiency and reduce time-consuming tasks and the risk of error in production, support, procurement and other areas.

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CIO 100 Award winners prove the transformative value of IT

CIO Business Intelligence

A risk-limiting audit (RLA) is one audit type used for election verification. The Behavioral Health Acuity Risk (BHAR) model leverages a machine learning technique called random forests, which can be natively hosted in the electronic health record and updated in near-real time, with results immediately available to clinical staff.

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How to supercharge data exploration with Pandas Profiling

Domino Data Lab

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task.