In this week’s roundup, learn how a machine learning (ML) model predicts COVID-19 severity and mortality. Understand how data-first marketing will help you to stop wasting 30% of your budget. Discover the top 10 data and analytics trends for 2021, and get 18 interesting data science podcast recommendations. Finally, explore how ML and mathematical optimization was used to help automate a complex campaign selection process and drastically increase acquisition rates.

Machine Learning Model Predicts COVID-19 Severity, Mortality

By Samantha McGrail, contributing writer for

A machine learning model developed at Mount Sinai accurately identified at-risk COVID-19 patients and underlying relationships, predicting outcomes in 4,000 patients. Looking at patient characteristics at admission, they were able to predict critical events or mortality at three, five, seven, and ten days from admission. Learn why this is important in treating COVID-19.


18 Must-Subscribe Data Science Podcasts

by Stephen Gossett, contributing writer for

Need some new podcast shows to dive into? Look no further. Here is a comprehensive list of great data science podcasts that you can sink your teeth into. From data science to machine learning to artificial intelligence to general interest, you can immerse yourself into the audio world of data science for hours. 


Top 10 Data and Analytics Trends for 2021

By Jessica Davis, contributing writer for

Enterprise organizations have long since adopted the concepts of big data, machine learning, and artificial intelligence. Executing these concepts and bringing them to life has always been a bit slow to come to fruition. However, last year Gartner reports that AI deployments to production increased to 19%. This article covers 10 strategic technology trends designed to take enterprises from “crisis to opportunity,” which Gartner presented at its recent Gartner IT Symposium.


Data-First Marketing: A Strategy to Stop Wasting 30% of Your Budget

By Scott Vaughn, contributing writer for

Most marketing professionals would agree that strategically utilizing data is an important foundation to an effective marketing and sales plan. Yet most B2B teams fail to conquer data readiness and governance. It’s time to commit to getting your data right. This commitment makes people, programs, and results better. That sounds great, but what does “right” really mean in today’s landscape?


Case Study: Mathematical Optimization & Machine Learning

Featured on

AARP had a lengthy, complex multi-channel monthly campaign selection process as part of the ongoing effort to bring on new members. The desire was to find a more rigorous analytic solution to improve program efficiency, optimize acquisition, and process automation. Learn how the Lityx team utilized machine learning and mathematical optimization to do just that, resulting in a 90% increase in acquisition and a much speedier, more efficient process.


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