NEXT SEMINAR:
REGISTER HERE: https://mycri.cri.uchicago.edu/educations/trainings/80/register/
Enhancing Clinical Data Science: Machine Learning & Advanced Techniques for Novel Insights in Clinical Research
Wednesday, January 14th | 9:00am – 10:15am CST
Knapp Center for Biomedical Discovery (KCBD) Auditorium 1103
Speaker: Ilaria Lonoce, PhD
The Center for Research Informatics invites you to an upcoming seminar showcasing how advanced data science techniques can reveal meaningful insights from clinical data that often go overlooked with standard analytical methods. Join us to discover how these novel analytical tools are expanding the possibilities in clinical research.
Using real-world, publicly available clinical case studies, this seminar will explore methods to:
- analyze word frequencies using text mining tools
- identify key topics and uncover hidden themes within medical narratives.
- visualize multidimensional data to detect patterns and emerging groups
- apply machine learning classifiers to build more robust predictive models using enriched features
This seminar will take place at Knapp Center for Biomedical Discovery (KCBD) Auditorium 1103. 900 E 57th, Chicago, IL 60637. also, via Zoom. Registration is required for all attendees, whether you plan to attend in person or via Zoom. Please ensure you register using the provided link by 9am on Tuesday, January 13th. Zoom meeting information will be sent via calendar invite to registrants one day prior to the session. Participation is open to University of Chicago, UCM, and Pritzker School of Medicine faculty, staff, and students.
About the speaker: Ilaria Lonoce is a Clinical Data Scientist at the Center for Research Informatics where she applies her data science and statistical expertise to support clinical research through healthcare data analysis, predictive modeling, and the translation of complex datasets into actionable insights.
Before joining the CRI, she served as a postdoctoral researcher in the Department of Astronomy and Astrophysics at the University of Chicago. She previously completed both her PhD and a postdoctoral fellowship at the Astronomical Observatory of Brera in Milan, Italy, and holds a bachelor’s and master’s degree from the University of Milan.
With a foundation in observational data analysis and spectroscopic studies of near and distant galaxies, Ilaria brings a rigorous data-driven perspective to clinical research.
About the series: Since 2012, the Center for Research Informatics has offered free training sessions for the University of Chicago community in informatics research tools and techniques. Topics include REDCap, clinical data, bioinformatics analysis, data visualization, high performance computing, grant preparation, and more. To hear about upcoming seminars, sign up for our email list at https://cri.uchicago.edu/seminar-series.
Feedback Survey: We value your feedback and would appreciate if you would take a moment to complete our quick survey. Your insights will help us enhance our seminars and ensure they provide the best possible learning experience. Additionally, we welcome your suggestions for future seminar topics and any areas you’re interested in exploring further.
Questions? Contact Janaya Lee at janayalee@bsd.uchicago.edu.
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PAST SEMINARS
We archive our past training seminars here, including links to the content if it is available.
| Date | Topic | Seminar Title | Content |
|---|---|---|---|
| April 2025 | Bioinformatics | Spatial Transcriptome Analysis | Spatial Transcriptomics Workshop |
| February 2025 | Bioinformatics | Bulk-RNAseq Pipeline | Bulk-RNAseq Pipeline Hands-on Training |
| October 2024 | CRI/BSDIS | Overview of CRI and BSDIS | CRI/BSDIS IT Expo Session |
| August 2024 | Bioinformatics | Using R Bioconductor packages for bulk RNA-seq DE analysis | Using R Bioconductor packages for bulk RNA-seq DE analysis |
| January 2024 | Bioinformatics | Introduction to Linux Command Line for Bioinformatics | |
| November 2023 | Data Analytics | Showcase of Reseach Project: NLP to Identify Mental Illness and Substance Use Factors in Clinical Notes | Case Illustration of NLP in a Research Project |
| November 2023 | Bioinformatics | Workshop Series: Part One Introduction to 10x Genomics Sequencing Protocols | Single Cell RNA-seq Data Analysis |
| February 2023 | REDCap | Introduction to REDCap | Introduction to REDCap |
| January 2021 | Data Analytics | Case Illustrations of NLP in Clinical Research | |
| May 2020 | HPC | Introduction to NVIDIA Parabricks | |
| April 2020 | REDCap | Making the Most of REDCap: All About Surveys | All About REDCap Surveys |
| February 2020 | REDCap | Making the Most of REDCap: Beyond the Basics | REDCap Beyond the Basics |
| January 2020 | HPC | Overview of CRI Computing Infrastructure | Overview of CRI Computing Infrastructure |
| May 2019 | Bioinformatics | Advanced Interactive Data Visualizations with Python | |
| March 2019 | Data Analytics | Using Natural Language Processing in Clinical Data Analytics | Using NLP in Clinical Data Analytics |
| February 2019 | Bioinformatics | Introduction to Reproducible Research via R Markdown | |
| December 2018 | Grant Preparation | Including Informatics in Grant Applications | Including Informatics in Grant Applications |
| November 2018 | Clinical Data | Using the CRDW and Cohort Discovery Tools | CRDW and Cohort Discovery |
| October 2018 | Guest Talk | Introduction to the Human Imaging Research Office | Introduction to HIRO |
| September 2018 | HPC | Parallel Computing 101 | Parallel Computing 101 |
| August 2018 | Grant Preparation | Including Informatics in Grant Applications | Including Informatics in Grant Applications |
| May 2018 | Clinical Data | Using the CRDW and Cohort Discovery Tools | CRDW and Cohort Discovery |
| April 2018 | HPC | CRI Infrastructure and New Parallel Storage | CRI Infrastructure and New Storage |
| March 2018 | Bioinformatics | Introduction to IPython and Pandas for Bioinformatics | iPython and Pandas |
| February 2018 | Clinical Data | Statistical Modeling with Clinical Data | Statistical Modeling - Methods Statistical Modeling - CRDW |
| December 2017 | Grant Preparation | Including Informatics in Grant Applications | Including Informatics in Grant Applications |
| November 2017 | HPC | Computing with the CRI: Storage, HPC, and Virtual Servers | Computing with the CRI |
| October 2017 | Bioinformatics | Biological Interpretation of Gene, Transcript, and Protein Expression Data with IPA | Biological Interpretation with IPA |
| September 2017 | Data Analytics | Using NLP in Clinical Data Analytics | NLP in Clinical Research |
| August 2017 | Grant Preparation | Including Informatics in Grant Applications | Informatics in Grants, Part 1 Informatics in Grants, Part 2 |
| May 2017 | Bioinformatics | Genomics Data Visualization | Genomics Data Visualization |
| April 2017 | HPC | HPC Workshop: Advanced | HPC: Advanced |
| April 2017 | HPC | HPC Workshop: Beginner | HPC: Beginner |
| November 2016 | Bioinformatics | Biological Interpretation of Gene, Transcript, and Protein Expression Data with IPA | -- |
| November 2016 | Clinical Data | Optimizing Data Requests for the CRDW | Optimizing CRDW Requests |
| October 2016 | HPC | Introduction to Gardner: The CRI's New HPC Cluster | Introduction to Gardner |
| April 2016 | Bioinformatics | Biological Interpretation of Gene, Transcript, and Protein Expression Data with IPA | -- |
| December 2015 | Bioinformatics | Annual Workshop: Bioinformatics Analysis of Integrative -Omics Data | Workshop Recap |
| October 2015 | Bioinformatics | Introductory Statistics with R | Introductory Statistics with R |
| September 2015 | Bioinformatics | Introduction to iPython and Pandas, Part II | iPython and Pandas, Part II |
| June and July 2015 | Bioinformatics | Introduction to iPython and Pandas, Part I | iPython and Pandas, Part I |
| May 2015 | Bioinformatics | Introduction to Python Programming, Part II | Introduction to Python, Part II |
| April 2015 | Bioinformatics | Introduction to Python Programming, Part I | Introduction to Python, Part I |
| March 2015 | Bioinformatics | Analysis of Affymetrix Microarray Data with R and Bioconductor | Analysis of Affymetrix Microarray Data |
| February 2015 | Bioinformatics, HPC | Introduction to CRI’s HPC Cluster for Bioinformatics Computing | Introduction to CRI's HPC Cluster |
| January 2015 | Bioinformatics | R Graphics for Bioinformatics | R Graphics for Bioinformatics |
| December 2014 | Bioinformatics | Annual Workshop: Bioinformatics Analysis of High-Throughput Genomics Data | Workshop Recap |
| October 2014 | Bioinformatics | Visual Exploration of Data with the Advanced R Graphics Library: ggplot2 | -- |
| September 2014 | Bioinformatics | Introduction to R Programming, Part II | Introduction to R Programming, Part II |
| August 2014 | Bioinformatics | Introduction to R Programming, Part I | Introduction to R Programming, Part I |
| July 2014 | Bioinformatics | Introduction to Python Programming, Part II | Introduction to Python, Part II |
| June 2014 | Bioinformatics | Introduction to Python Programming, Part I | Introduction to Python, Part I |
| May 2014 | Bioinformatics | Introduction to Linux Command Line for Bioinformatics | Introduction to Linux for Bioinformatics |
| April 2014 | Bioinformatics | Analyzing Illumina RNA-Seq Data with the CRI | Analyzing Illumina RNA-Seq Data with the CRI |
| March 2014 | Bioinformatics | Overview and Tutorial of Lynx: An Integrated Systems Biology Platform for Analysis of Multi-Gene Disorders | -- |
| February 2014 | Bioinformatics | Analysis of Illumina Microarray Data with R and Bioconductor | Analysis of Microarrays with R and Bioconductor |
| January 2014 | Bioinformatics | How to Use the CRI’s Computational Infrastructure for Bioinformatics Analysis | CRI Infrastructure for Bioinformatics, Part I and Part II |
| November 2013 | Bioinformatics | Introduction to Perl: Learning by Example | Introduction to Perl |
| October 2013 | Bioinformatics | Maximizing the Biological Interpretation of Gene, Transcript, & Protein Expression Data with IPA | -- |
| September 2013 | Bioinformatics | Introduction to Python Programming | Introduction to Python Programming |
| August 2013 | Bioinformatics | Introduction to R Programming | Introduction to R Programming |
| June and July 2013 | Bioinformatics | Introduction to Linux Command Line for Bioinformatics | Introduction to Linux Command Line for Bioinformatics |
| May 2013 | Bioinformatics | Analyzing Illumina ChIP-Seq Data with the CRI | Analyzing Illumina ChIP-Seq Data with the CRI |
| April 2013 | Bioinformatics, HPC | Introduction to CRI’s HPC Cluster for Bioinformatics Computing | Introduction to CRI's HPC for Bioinformatics |
| March 2013 | Bioinformatics | Analysis of Illumina Microarray Data with R and Bioconductor | Analysis of Microarrays with R and Bioconductor |
| February 2013 | Bioinformatics | Analyzing Illumina RNA-Seq Data with the CRI | Analyzing Illumina RNA-Seq Data |
| January 2013 | Bioinformatics | Analysis of Microarrays with R and Bioconductor | Analysis of Microarrays with R and Bioconductor |
| November 2012 | Bioinformatics | Analyzing Illumina Whole Exome Data with the CRI | Analyzing Illumina Whole Exome Data with the CRI |
| September 2012 | Bioinformatics | Galaxy: Web-based Bioinformatics Analysis & RNA-Seq Workflow Management | Galaxy: Web-Based Bioinformatics Analysis |
| August 2012 | Bioinformatics | Analyzing Illumina RNA-Seq Data with the CRI | Analyzing Illumina RNA-seq Data |
| July 2012 | Bioinformatics | Analysis of Microarray Data with R and Bioconductor | Analysis of Microarrays with R and Bioconductor |
