Health Analytics Collaboratory (HAC) Alzheimer's Disease (AD) Study

• Table of contents
• Overview
• R Code
• Team
• Acknowledgments
• References

The Health Analytics Collaboratory (HAC) is an open incubator for collaboration and digital scholarship that emphasizes team-based transdisciplinary data science and advanced health analytics. A core mission of HAC is to foster integration of innovative research, development, education and training, and outreach in data and health sciences.

The examples, demonstrations and simulations are designed, built, implemented and validated in the R environment. See the code folder.

Ivo D. Dinov, Marcelline Harris, Michelle Aebersold, Patti Abbott, Olga Yakusheva, Matt Davis, Kate Potempa, Marita Titler, Rob Ploutz-Snyder, Christine Anderson, Cooper Stansbury, Haiyin Liu, Bingxin Chen, Patricia Hurn.

This work is supported in part by NIH grants P20 NR015331, P50 NS091856, P30 DK089503, P30AG053760, UL1TR002240, and NSF grants 1734853, 1636840, 1416953, 0716055 and 1023115. Students, trainees, scholars, and researchers from SOCR, BDDS, MNORC, MIDAS, MiCHAMP, MADC, MICHR, and the broad R-statistical computing community have contributed ideas, code, and support.

CARD References:

1. Wu Y, Rosenbloom ST, Denny JC, Miller RA, Mani S, Giuse DA, Xu H. Detecting abbreviations in discharge summaries using machine learning methods. AMIA Annu Symp Proc. 2011, 1541-9. [PMCID: PMC3243185]
2. yonghuiwu / card — Bitbucket [Internet]. [cited 2019 Jun 12]. Available from: https://bitbucket.org/yonghuiwu/card/src/master/
3. Wu Y, Denny JC, Trent Rosenbloom S, Miller RA, Giuse DA, Wang L, et al. A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD). J Am Med Inform Assoc. 2017 Apr 1;24(e1):e79–86.
4. Wu Y, Rosenbloom ST, Denny JC, Miller RA, Mani S, Giuse DA, et al. Detecting Abbreviations in Discharge Summaries using Machine Learning Methods. AMIA Annu Symp Proc. 2011;2011:1541–9.
5. Xu H, Stetson PD, Friedman C. Methods for Building Sense Inventories of Abbreviations in Clinical Notes. J Am Med Inform Assoc. 2009 Jan 1;16(1):103–8.