Upcoming +DS COVID-19 Data Science Seminars

Data Science Methods With Direct Application to COVID-19
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Jun 15, 2020

About the Series

Join +Data Science for an eight-week series on data science methods with direct applications to the COVID-19 pandemic and learn from Duke experts about the state-of-the-art in these one-hour virtual sessions.

Upcoming Seminars

Tuesday, June 30 at 4:00 p.m. EST
 

Key elements of the analytical toolbox for understanding COVID-related data

The ability to make rapid, data-driven decisions is a key component for prioritizing COVID-19 research, treatments, and public health initiatives.

Tuesday, June 30, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Matthew Hirschey

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Tuesday, July 7 at 4:00 p.m. EST
 

Natural language processing and understanding the evolving COVID literature

There has been an explosion of scientific literature on COVID-19 in the past several months with thousands of articles already available.

Tuesday, July 7, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor David Carlson

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Tuesday, July 14 at 4:00 p.m. EST
 

Molecular methodology connected to COVID data

Molecular analysis of gene expression, microbiome, and proteomics data aims to understand biological processes by leveraging high-throughput technologies and data science. Aided by subject matter expertise, this combination has resulted in accelerated discoveries in health and disease.

Tuesday, July 14, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Ricardo Henao

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Tuesday, July 21 at 4:00 p.m. EST

Simple introduction to deep learning

A key aspect of analysis of data involves classification and regression; these play a key role in the analysis of many types of data connected to COVID-19. To perform such analyses, one typically must extract features from the data, with which classification/regression is performed.

Tuesday, July 21, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Lawrence Carin

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Wednesday, July 22 at 4:00 p.m. EST

Introduction to PyTorch computational platform for deep learning

PyTorch is an open source framework for building neural networks. In this lesson, we will build a foundational understanding of PyTorch by developing a simple neural network, the Multilayer Perceptron (MLP).

Wednesday, July 22, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Matthew Kenney

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Thursday, July 23 at 4:00 p.m. EST

PyTorch for image analysis with deep learning

The goal of computer vision is for computers to be able to understand visual content (e.g. images, videos, 3D, stereo), usually for the purpose of making predictions (classification, detection, captioning, generation, etc.).

Thursday, July 23, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Timothy Dunn

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Tuesday, July 28 at 4:00 p.m. EST

Analysis of chest CT imaging data and connection to COVID diagnosis

Medical image analysis with machine learning holds immense promise for accelerating the radiology workflow and benefiting patient care. Chest computed tomography (CT) is a medical imaging technique that produces a high-resolution volumetric image of the heart and lungs.

Tuesday, July 28, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Rachel Draelos

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Tuesday, August 4 at 4:00 p.m. EST

Using data science to optimize scheduling elective procedures in the time of COVID

On the day before the session, all registrants will receive an e-mail with a link and meeting information.

Tuesday, August 4, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Benjamin Goldstein

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Tuesday, August 11 at 4:00 p.m. EST

Causal inference for quantifying the efficacy of potential COVID medications and vaccines

We will overview several important issues in causal inference methods for evaluating the comparative effectiveness and efficacy of potential COVID medications and vaccines. These issues cover both design and analysis of randomized trials, natural experiments, and observational studies.

Tuesday, August 11, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Fan Li

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Tuesday, August 18 at 4:00 p.m. EST

The opportunity for wearables for early COVID detection

On the day before the session, all registrants will receive an e-mail with a link and meeting information.

Tuesday, August 18, 2020 | 4:00 PM – 5:00 PM
Location: Virtual, Classroom
Instructor: Professor Jessilyn Dunn

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View seminar series on +Data Science ›

 

Contact: 

Shelley Rusincovitch, MMCi
Associate Director of Informatics, Duke Forge
shelley.rusincovitch@duke.edu
(919) 668-5954