NCI Data Jamboree (Project Abstract Submission): Submission #42
Submission information
Submission Number: 42
Submission ID: 189078
Submission UUID: 04c6bd48-3aa1-43f4-9b43-eb6a839dd7be
Submission URI: /nci/datajamboree/abstractsubmission
Submission Update: /nci/datajamboree/abstractsubmission?token=pcb-gBNOJDHv2CgR-fDAv1wzactxF_JoQapHcPyPVKY
Created: Mon, 07/27/2026 - 10:18
Completed: Mon, 07/27/2026 - 10:18
Changed: Mon, 07/27/2026 - 10:18
Remote IP address: 10.208.28.116
Submitted by: Anonymous
Language: English
Is draft: No
Webform: NCI Data Jamboree (Abstracts)
Submitted to: NCI Data Jamboree (Project Abstract Submission)
| First Name | Nadia |
|---|---|
| Middle Initial | |
| Last Name | Howlader |
| Degree(s) | Ph.D. |
| Position/Title/Career Status | Director, Real World Evidence Oncology |
| Organization | Boehringer Ingelheim |
| Organization Address | Ridgefield, Connecticut, USA |
| nadia.howlader@boehringer-ingelheim.com | |
| List of Additional Authors |
|
| Abstract Category | Developing tutorials, workbooks, infographics, or creative use of data for educational and engagement purposes |
| Abstract Keywords | Reproducibility, AI Readiness, Real-World Evidence, Epidemiology, Electronic Health Records |
| Abstract Title | Assessing Real-World Data Quality for Reproducible Research and AI Readiness |
| Abstract | I am an epidemiologist with expertise in real-world evidence, oncology research, and the analysis of large healthcare datasets including electronic health records, claims, and cancer registries. I am interested in participating in this project to help evaluate data quality dimensions that support reproducible research and trustworthy AI applications. Through the jamboree, I hope to collaborate with multidisciplinary experts to develop practical approaches for assessing data completeness, consistency, and fitness for purpose, while advancing best practices for AI-ready healthcare data. |