Real-world data (RWD) can come from a variety of sources, including claims, electronic health records, biobanks, genomics tests, and imaging modalities. Increasingly, it is coming from digital data through electronic health and mobile health modalities. Recent events have pushed innovation in the use of RWD to maximize the value of real-world evidence in an era of big data, data science, and artificial intelligence.
artificial intelligence
Stats4Good: Big Data Methods for Data for Good
Data for Good looks at the big data revolution and how it affects our approaches to problem-solving, as well as examples of how big data is being applied.
Gabriela de Queiroz
Gabriela de Queiroz initially studied electrical engineering but fell in love with statistics after spending a semester in the US. She went on to complete her master’s in epidemiology and then became a data scientist, intrigued by how statistics and computer science were being used together in industry. Her great passion for sharing knowledge and connecting with people inspired her to create R-Ladies, a group that focuses on bringing more diversity into the R community. She recently started AI Inclusive, whose mission is to increase the representation and participation of gender minority groups in artificial intelligence.
Claudia Perlich
Claudia Perlich was born near Leipzig, East Germany. Her father—having worked on replicating the IBM 360—foresaw that computer-related skills would be in demand, so—on his advice—Claudia studied computer science. Today, she is an adjunct professor at NYU’s Stern School of Business and a senior data scientist at Two Sigma. Among the aspects of data science she appreciates most is the subtle skill of trying to find what she calls the “little quirks” in a data set. “It’s like doing detective work,” she says.
ASA to Cosponsor AI in Clinical Drug Development Symposium in May
The Pfizer/ASA/Columbia University Symposium on Risks and Opportunities of AI in Clinical Drug Development aims to advance the use of artificial intelligence (AI) in drug development and deployment.
Using Big Data in Precision Medicine
Experts from pharma, biotech, government, academia, and technology providers discuss the opportunity to use big data to find the right drug at the right time using the right target.