Improved LISA Analysis for Zero-Heavy Crack Cocaine Seizure Data
Local Indicators of Spatial Association (LISA) analysis is a useful tool for analyzing and extracting meaningful insights from geographic data. It provides informative statistical analysis that highlights areas of high and low activity. However, LISA analysis methods may not be appropriate for zero-heavy data, as without the correct mathematical context the meaning of the patterns identified by the analysis may be distorted. We demonstrate these issues through statistical analysis and provide the appropriate context for interpreting LISA results for zero-heavy data.
Large language models and synthetic health data: progress and prospects
There is growing interest in the application of machine learning models and advanced analytics to various healthcare processes and operations, including the generation of new clinical discoveries, development of high-quality predictions, and optimization of administrative processes. Machine learning models for prediction and classification rely on extensive and robust datasets, particularly for deep learning models common in health, creating an urgent need for large health datasets.
Smith School’s Bjarnadóttir Earns Highest Icelandic State Honor for Research Impact
Margrét Bjarnadóttir, associate professor at the Smith School, was awarded the Knight’s Cross of the Icelandic Order of the Falcon for transformative research on pay equity.
Smith School Hosts Workshop on AI and Analytics for Social Good
On May 10, 2024, the University of Maryland’s Smith School hosted the AI and Analytics for Social Good Workshop, featuring experts from leading institutions discussing the use of analytics for social impact, including misinformation, platform regulation, and educational analytics.
Mapping the Cocaine Supply Chain
A team of UMD researchers is studying how to map and disrupt the cocaine supply chain. The research is supported by the National Science Foundation (NSF) and is led by the Smith School’s S. Raghu Raghavan.
Analytics Are Key to Ending Gender Pay Inequity
Organizations often use the inexpensive and expedient approach of raising the salaries of the most underpaid women to bring about women’s pay parity with men. University of Maryland Robert H. Smith School of Business Associate Professor Margrét Bjarnadóttir says there are two reasons why this doesn’t work, “inequity isn’t usually equally spread throughout the whole organization and typically there’s a lack of well-paid women.
Under Sanction or Not: Female Doctors Face Bias in Online Reviews
Many people use online reviews when looking for a doctor, and since the pandemic began it’s become an even more popular way to find medical care. Margrét Bjarnadóttir and her co-authors have examined the link between online patient reviews and quality of care.
A ‘30 Under 30’ Recipient, on Embracing Challenges
For Loop CTO Ali Salhi, MS in Business Analytics ’18, Maryland Smith was a place to learn about the importance of learning through challenges.
People Analytics for an Equitable Workplace
“People analytics” – traceable to 1911’s The Principles of Scientific Management, which sought to apply engineering methods to managing people – has exploded with advances in computer power, statistical methods and artificial intelligence (AI).
Maryland Smith Launches Data Science and Business Analytics Certificate Program
The University of Maryland’s Robert H. Smith School of Business is launching a nine-month, fully online certificate program designed for technical and non-technical professionals interested in leveraging data to draw insights and drive smarter decision-making for their organization.