Stanley Manne Children's Research Institute

Data Science and Analytics Support Services

Data science seeks to gain useful insights from diverse data sets by employing a range of computational analytics and visualization techniques. As part of the Quantitative Science pillar at Stanley Manne Children’s Research Institute, our team of data scientists and report analysts work closely with data engineers and informatics analysts to support innovative pediatric research across Manne Research Institute. Our team brings a rich variety of expertise, including physiological data analytics, machine learning (ML) and artificial intelligence (AI), predictive analytics, remote patient monitoring analytics, natural language processing (NLP), data fusion, and comprehensive support for big data analytics. We specialize in utilizing advanced analytics tools such as Python, MATLAB, R, Databricks and Spark, coupled with sophisticated visualization techniques to elucidate complex biological and clinical phenomena. 

Engagement Options

  • Consultation: We love to brainstorm with researchers and provide education about advanced analytical and computational methods. Consultations are free.
  • Project Services: Our team is also available for well-defined, discrete analytics projects. These services are billed at our hourly rate.
  • Grant Development: We encourage researchers to develop a close collaboration early in the process of research design and proposal development. Assuming funded inclusion of our team members or services in the ultimate proposal, these services are free.
  • Grant-funded Analytics Support: Named personnel (and partial FTE) managed by Quantitative Science support funded research. 

Example Services

  • Structured Tabular Data Queries: Extracting data from clinical and administrative databases for tabular datasets that can be used for exploratory analysis, cohort discovery, statistical analysis, visualization or other research-related needs.
  • Physiological Data Analytics: Leveraging a rich historical database of critical care bedside monitor data to uncover vital insights into patient health and disease progression. Our data includes 10+ years of continuous raw waveforms, vitals, alarms from Lurie Children’s PICU, NICU, CICU and some NICU beds at Northwestern Medicine's Prentice Women’s Hospital.
  • Imaging Analytics: Analyzing visible light and other sensor arrays, including video and volumetric techniques that can be used to enrich discrete clinical data for predictive modeling.
  • Machine Learning and Predictive Analytics: Developing and deploying ML models for predicting clinical (and operational) outcomes within the EHR.
  • Remote Patient Monitoring: Employing remote health (and environmental) data to enhance patient monitoring and care delivery.
  • Natural Language Processing: Extracting and analyzing of valuable information from unstructured text within medical records, literature, and patient feedback using both traditional NLP techniques and advanced large language models.
  • Big Data Support: Providing infrastructure and expertise to manage and analyze large-scale healthcare data sets.
  • Advanced Analytics: Utilizing state-of-the-art analytics tools (Python, MATLAB, R, Spark) for in-depth data analysis and modeling.
  • Advanced Data Visualization: Creating intuitive and interactive visual representations of complex data sets to facilitate understanding and decision-making. 

Service Rates

View details on Data Science and Analytics Support service rates for fiscal year 2025.

How to Engage with Data Science and Analytics Support Services 

Researchers can request data science and analytics support by completing a Quantitative Science intake form.

Contact Information 

For help with your data science questions, please email Quantsci@luriechildrens.org.