A cornerstone of therapeutics and vaccine pipelines, life sciences imaging data comprises close to 70% of all clinical data worldwide. As organizations rely more on advanced imaging modalities, establishing an effective IT infrastructure to support that data is critical. How can you transform your c
Discovering new drugs requires tremendous investment and the ability to face difficult odds, but advances in computing and data science can expedite the process and reduce time-to-market. In silico research and data-driven insights promise to both deliver new therapeutic targets faster and also re-p
Genomics data is a critical tool for preventing diseases and designing individualized treatment plans in modern medical practices. With the advent of new analysis techniques like next-generation sequencing (NGS), precision medicine researchers can acquire exponential amounts of genomic data and defi
Utilize a modern data infrastructure to streamline clinical trials and accelerate time-to-market. Only 12% of drug candidates successfully navigate the three phases of a clinical trial. To improve the odds, the biopharma industry is turning to intelligent clinical trials informed by comprehensive, r
NHS England’s National Clinical Lead for Innovation, reveals the secrets of his success. And his spectacular failures!
For as long as there have been humans, there has been an understanding of why people become ill, and how to help them. I imagine the earliest man to have known the basics: fire = burns, falling from a tree = injury, snow or ice = reduced swelling
Yesterday (29 September), fellow delegates shared their respective experiences and thoughts at the AIMed Healthcare Executives virtual conference on the key requirements for successful implementation of artificial intelligence
No time for guessing game. Three things payers need to consider if they are to survive the impact of deferred care. A recent Kaiser Family Foundation survey found that nearly half of all Americans say they or someone they live with has delayed care since COVID started. The why behind this is two-fol
Nothing beats the stimulation of designing and building a machine learning model, but it has become more obvious in recent years that the process can be a tedious one too. The call for a more inclusive, liable, and transparent artificial intelligence (AI) has never been louder. Yet, in the absent of
