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Commercial Analytics and It’s Defining Role In Pharma Marketing

Pharma companies are working hard to build effective patient access programs and implement an effective commercial strategy around it. Expiring patents and competitive pressure is a real challenge and companies need to explore opportunities with the help of the vast amounts of data they own. Big Data and Analytics capabilities are helping companies define that strategy and execute a plan, which will help them succeed. Our friends over at Prescriber360 put together the infographic below containing facts and figures to emphasize the need of a well-planned analytics strategy.

Why Big Data Means Better Health

In this special guest feature, Souvik Das, Senior VP of Engineering at Grand Rounds, discusses how big data will open up the opportunity for physicians to impact patients anywhere in the world, all from a single interface or digitized platform. In turn, patients will also become better informed of the right doctor and treatment path for their unique needs.

Data-Driven Healthcare: A Proactive Revolution

In this special guest feature, Richard Proctor, GM of Global Healthcare at Hortonworks, discusses how big data is enabling key healthcare organizations including UNOS, MD Anderson and Arizona State University to manage chronic diseases, improve overall member health, reduce costs, and manage clinical and financial risk.

Artificial Intelligence App Game Changer for Health Care Technology in the US

Health technology company Ada has brought a new artificial intelligence (AI) powered health companion to the US, providing Americans with a more personalized way to assess and monitor their health. Designed to grow smarter as users engage with it, Ada’s intelligence not only offers users a sophisticated and tailored health assessment, ­ it also supports […]

Government Sponsored Data Analytics in Healthcare and Life Sciences

The insideBIGDATA Guide to Data Analytics in Government provides an in-depth overview of the use of data analytics technology in the public sector. Focus is given to how data analytics is being used in the government setting with a number of high-profile use case examples. This is the third in a series of articles providing content extracted from the guide. The topic for this segment is government sponsored data analytics in healthcare and life sciences.

FDA’s Next Frontier: Regulating Machine Learning in Clinical Decision Support Software

In this special guest feature, Bradley Merrill Thompson, a partner in the Washington DC office of law firm Epstein Becker & Green and Chairman of the Board of the firm’s consulting affiliate EBG Advisors, starts a compelling and timely conversation on the FDA’s approach to regulating machine learning.

4 Ways AI Is Changing Healthcare

In this contributed, Anthony Coggine, HR professional turned business analyst. provides four ways that artificial intelligence (AI) is changing the healthcare industry.

4 Ways Artificial Intelligence is Revolutionizing Healthcare

In this special guest feature, Prashanth Kini, Vice President and Head of Product, Healthcare for Ayasdi provides four real-world examples where machine intelligence is helping provider organizations transform into learning health systems that are continually improving performance.

4 Pros and Cons of the Medical IoT

In this contributed article, technology writer and blogger Kayla Matthews provides 4 pros and cons of the medical IoT. IoT has the potential to change the medical industry from the ground up, though time has not yet determined if that change is going to be a positive or negative one.

Uncovering Opportunities at the Intersection of Public and Private Data

In this special guest feature, Hicham Oudghiri, CEO and Co-Founder at Enigma, discusses how data analysis as a tool for solving problems requires an understanding that the answer lies within the data set, either in the form of an insight or actionable anomaly. As businesses turn to analytics more to solve their everyday issues, it is important to understand what data can and can’t do, and to understand how to identify which data sets in a sea of data can help solve the problem at hand.