# Introduction

<figure><img src="https://1320397393-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FS7ARvJIKiVWytaXqeV13%2Fuploads%2FQ0Dv2ts54IxsOhB0uHPa%2Fcodiac_sans_serif_fall.png?alt=media&#x26;token=362ba145-240a-4ae5-ab83-92af2f685fb5" alt=""><figcaption></figcaption></figure>

Welcome to the <mark style="color:blue;">**C**</mark>ompendium <mark style="color:blue;">**O**</mark>f <mark style="color:blue;">**D**</mark>ata science <mark style="color:blue;">**I**</mark>nformatics <mark style="color:blue;">**I**</mark>mplementation science <mark style="color:blue;">**A**</mark>rtificial intelligence and <mark style="color:blue;">**C**</mark>omputing for Health (CODIAC for Health)!

CODIAC for Health was created to support research and education activities in Rhode Island involving health data, computing, and technology. This community resource aims to provide the requisite knowledge and skills for advancing artificial intelligence in health, clinical and translational research, and learning health systems.&#x20;

CODIAC for Health is a living resource that is organized in chapters covering topics, methods, and resources relevant to health informatics, implementation science, and data science. The chapters can be navigated using the [**Table of Contents**](https://docs.bcbi.brown.edu/codiac-for-health/table-of-contents) or menu in the upper left corner.

<table><thead><tr><th width="307">Chapter</th><th>Description</th></tr></thead><tbody><tr><td>Foundations</td><td>Overview of topics with links to references and resources for learning more.</td></tr><tr><td>Observational Research with EHR Data</td><td>Best practices, pipelines, and national resources. <br><em><mark style="color:yellow;">More to come!</mark></em></td></tr><tr><td>Computing Skills</td><td>Unix, Julia, Python, R, and Other Basics<br>SQL, UML, HTML, etc. - <em><mark style="color:yellow;">Forthcoming!</mark></em></td></tr><tr><td>URSA Initiative in Rhode Island</td><td>Summary of local services and resources. <br><em><mark style="color:yellow;">More to come!</mark></em></td></tr><tr><td>Health Data and Data Standards</td><td><em><mark style="color:yellow;">Forthcoming!</mark></em></td></tr><tr><td>Artificial Intelligence for Health</td><td><em><mark style="color:yellow;">Forthcoming!</mark></em></td></tr><tr><td>Exercises and Case Studies</td><td><em><mark style="color:yellow;">Forthcoming!</mark></em></td></tr></tbody></table>

### Feedback

Feedback and corrections are welcome, which can be sent directly to URSA Services and Support (<ursa-help@brown.edu>).

### Acknowledgments

CODIAC for Health is supported in part by Institutional Development Award Number [U54GM115677](https://reporter.nih.gov/search/OLbM6zSh902XwLY-wpnT8A/project-details/10929374) from the National Institute of General Medical Sciences of the National Institutes of Health, which funds Advance Rhode Island Clinical and Translational Research (Advance RI-CTR). Its predecessor, the Biomedical Informatics and Data Science Skills (BIDSS) Manual was funded in part by [U54GM115677](https://reporter.nih.gov/search/OLbM6zSh902XwLY-wpnT8A/project-details/10929374) and [R25MH116440](https://reporter.nih.gov/search/9QnPsQG_vUKizzkXwCcAPw/project-details/9780587). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Parts of CODIAC for Health involve use of computational resources and services provided by the Center for Computation and Visualization (CCV) at Brown University.<br>


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