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--- | ||
format: pdf | ||
author: John Doe | ||
title: My fancy presentation | ||
author: Michael Throolin | ||
title: My fancy report on FIDDLE | ||
subtitle: For PHS 7045 | ||
--- | ||
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# Section 1 | ||
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## Sub-section 1 | ||
## Introduction | ||
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FIDDLE stands for a "**F**lex**i**ble **D**ata-**D**riven Preprocessing Pipe**l**in**e**." This acronym is a bit of a stretch, but it is a useful tool for preprocessing data to obtain features for machine learning algorithms. | ||
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The FIDDLE algorithm has been developed in Python [link to the github repo](https://github.com/MLD3/FIDDLE), but I would like to implement it in R for the purposes of this class final project. | ||
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## Description of the solution plan | ||
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## Preliminary results | ||
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```{r} | ||
#| label: some-code | ||
library(MASS) | ||
``` | ||
``` | ||
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## Citations: | ||
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@article{FIDDLE, | ||
author = {Tang, Shengpu and Davarmanesh, Parmida and Song, Yanmeng and Koutra, Danai and Sjoding, Michael W and Wiens, Jenna}, | ||
title = "{Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data}", | ||
journal = {Journal of the American Medical Informatics Association}, | ||
year = {2020}, | ||
month = {10}, | ||
doi = {10.1093/jamia/ocaa139}, | ||
} |
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