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<!DOCTYPE HTML>
<!--
Solarize by TEMPLATED
templated.co @templatedco
Released for free under the Creative Commons Attribution 3.0 license (templated.co/license)
-->
<html>
<head>
<title>Current Research</title>
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<h1><a id="logo">Goldenberg Lab</a></h1>
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<li class="active"><a href="index.html">Home</a></li>
<li><a href="current.html">Current Research</a>
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<li><a href="contact.html">Contact</a></li>
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<header class="major">
<h2>Current Research</h2>
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<p>
Most diseases are complex, depending on multiple genetic, environmental and lifestyle factors. High throughput experiments facilitate data collection allowing some of that complexity to be captured. Different types of data provide varied, often complementary information about the same biological phenomenon. For example, genomic analyses of copy number alterations in cancer cells report on losses and amplifications of genomic regions, while genome wide RNA expression data provide evidence on the impact of genomic and environmental events on the internal wiring of the cell. In our lab we work on creating machine learning methods that make such data useful for clinical diagnosis.
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<a href="covid.html" class="image fit"><img src="images/portfolio/covid_new.png" alt=""></a>
<p>Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds</p>
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<a href="wbmri.html" class="image fit"><img src="images/portfolio/9_new.jpg" alt=""></a>
<p>Generative Models for Pediatric wbMRI</p>
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<p>Deep Reinforcement Learning</p>
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<p>Dropout Feature Ranking of Deep Learning Models</p>
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<a href="drug_response.html" class="image fit"><img src="images/portfolio/vae_new.png" alt=""></a>
<p>Drug Response Prediction</p>
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<p>Cardiac Arrest Prediction</p>
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<p>Similarity Network Fusion</p>
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<p>Graphical models for variant aggregation</p>
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