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Advanced Analytics | Artificial Intelligence | Fraud & Security Intelligence | Risk Management
Maíra Porto 0
SAS no Febraban Tech 2026: agenda de palestras

O SAS estará presente no Febraban Tech, um dos mais importantes eventos de tecnologia, inovação e negócios da América Latina.  Neste ano, o evento acontece nos dias 24, 25 e 26 de agosto, no Distrito Anhembi, reunindo líderes, especialistas e empresas para discutir como dados, analytics e inteligência artificial estão

Analytics | Programming Tips
Rick Wicklin 0
A visual introduction to the Genz method for computing multivariate normal probabilities

I've been working on a project that uses quasi-Monte Carlo (QMC) techniques to estimate probabilities for multivariate normal (MVN) distributions on finite or infinite rectangular regions. The goal is to enable SAS users to compute these probabilities accurately and efficiently. My implementation is based on a numerical technique called the

Advanced Analytics | Artificial Intelligence | Innovation
Amanda Barefoot 0
Personalization is becoming health care’s new standard

The consumerization of health care is no longer a future-state concept. It is here, and it is reshaping expectations faster than many organizations are prepared to meet. Patients today are not just recipients of care. They are consumers comparing experiences across industries. They expect the same level of personalization, convenience

Advanced Analytics | SAS Events
Sarah Myers 0
Turning patient no-show predictions into action

Every missed appointment affects more than one patient. It delays care, leaves valuable clinical time unused, disrupts schedules and creates additional work for care teams already operating under significant pressure. For health care organizations facing growing demand and limited resources, reducing patient no-shows can improve both patient access and operational

Artificial Intelligence | Data Management | Predictions
Lindsey Coombs 0
AI is as data does: Why data intelligence builds on data management

AI gets the spotlight. Data does the work. Across industries, organizations are racing to adopt large language models (LLMs), build AI assistants and explore autonomous agents. This ambition is understandable. AI promises faster decisions, new efficiencies and entirely new ways of working. But amid the excitement, many leaders are overlooking

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