Machine Learning in Clinical Trials and R or Python or Both? Pennsylvania USA May 2019

Details:

We are in the 21st century and have achieved a lot of milestones in the field of technology and medical (health care) industry. Yet as time is passing, the life of people is getting short and the reason behind that are new diseases.

Health is the most important factor for every living being, as the universe is made for humans to live and use all available natural resources present on the earth.

Here we will discuss four topics in short which will be the key points to be discussed as to how and why machine learning is important in clinical trials with “R” or “Python” or Both.

  1. Machine learning
  2. Clinical trial
  3. R or Python
  4. Deep learning

Thanks to this event’s sponsors IQVIA (https://www.iqvia.com/) and Linode (https://www.linode.com) for their generous support of DataPhilly! We couldn’t make DataPhilly happen without their help.

Two excellent talks on data science will be presented.

A.    Nan Li from IQVIA will talk on using deep learning techniques to find the most appropriate clinical investigator.

B.    Scott Jackson from Rstudio will address the debate of R vs Python by demonstrating the need for both.

Dr. Right: Optimizing Clinical Trials with the Most Appropriate Investigators

The success of clinical trials heavily depends on choosing top-enrolling investigators. I will be sharing how we integrate heterogeneous data, including the free-form text protocol data of clinical trials, investigators’ historical enrolling performance data, EHR data and so on, and our novel algorithms based on advances in deep learning and tensor mining.

About Nan Li

Nan Li is a Data Science lead at IQVIA, where he builds machine learning models to optimize clinical trials. He is passionate about solving human data science problems with Artificial Intelligence. He has both AI research and software development backgrounds.

Using R and Python Together Effectively

R is mainly used for statistical analysis while Python provides a more general approach to data science. R and Python are states of the art in terms of programming language oriented towards data science. Learning both of them is, of course, the ideal solution. Python is a general-purpose language with a readable syntax. Would like to hire Data Scientists contact us!

“Should I learn R or Python?” is a question you’ll hear frequently from beginner data scientists, who are eager to enter the field as rapidly as possible and focus on a unified toolset. Scott will be discussing how you can benefit from both languages’ strengths using Reticulate and Feather, how to think scientifically about your performance concerns using experimentation tools, and how you can successfully productionize polyglot data science projects.

About Scott Jackson

Scott Jackson is a software engineer at RStudio and an individual contributor to RStudio Connect. Scott has been writing software professionally for over 14 years and continues to do so, despite a brief career as a patent lawyer. Scott lives in Center City Philadelphia, roasts coffee for fun, and wants to know about fascinating open source stuff you have done or are thinking about doing.

Where & When

Wednesday, May 1, 2019
6:00 PM to 8:30 PM

IQVIA
1 IMS Dr · Plymouth Meeting, PA, USA

Source URL: https://www.meetup.com/DataPhilly/events/260120660/

Our Website Development Services: