2 Real World Examples: Using Real World Data for Commercial Pharmaceutical Product Insights
Here is a look at two pharmaceutical use cases where text mining has transformed real world data into real world evidence.
Drug Repurposing, Rare Diseases and Semantic Analytics
Drug repurposing could help find cures for rare diseases faster, but trawling through research is a time-consuming and resource-heavy task.
4 Keys to Modern Knowledge Engineering
After decades of research, knowledge engineering is resurfacing as an artificial intelligence-driven solution to collect, understand, and infer relationships from… Read more
Pharma Turns to Real World Evidence to Overcome the Odds
Real world evidence is used for post approval regulation and labeling purposes. But RWE has many more untapped uses that firms now appear keen to explore.
Machine Learning: Understanding the Difference Between Unstructured/Structured Data
For us non-scientists, machine learning can be a confusing concept. The first step is to identify the difference between unstructured and structured data.
How Enterprise Data Science Has the Potential to Impact Life Sciences
How can life sciences organizations transform large volumes of complex data into hypothesis-generating knowledge representation? Enterprise data science.
What is Value Data and Why Do Information Managers Need It?
Being armed with value data makes justifying R&D content spend significantly easier. Here are some types of value indicators to consider.
Enterprise Data Science: What It Is and Why It Matters
The ocean of digital assets available to the modern enterprise contains an enormous amount of untapped business value. The ability to exploit these digital assets could prove to be the single most important differentiator between leaders and laggards over the next decade.
2 Big Takeaways for Information Managers from the 2017 State of BI and Predictive Analytics Report
How, when, and why are organizations using business intelligence tools? A look inside Dresner Advisory Services’ 2017 Advanced and Predictive Analytics Market Study.
3 Steps to Turn Analytics into Actionable Insights
In order to get the insights you’re looking for, you have to have a clear idea of your goals beforehand.