AI Articles and Analysis about Business intelligence and analytics

This interview analysis is sponsored by MindBridge and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

 This interview analysis is sponsored by Arkestro and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

As technology advances, the lines between mobile applications and medical devices are blurring in ways that have healthcare leaders, software developers, and regulators alike facing new and unprecedented challenges.

Boeing, founded in 1916, is a global aerospace company and one of the largest aircraft manufacturers in the world. Headquartered in Arlington, Virginia, the company operates in commercial airplanes, defense, space, and security sectors. 

This interview analysis is sponsored by Capgemini and was written, edited, and published in alignment with our Emerj-sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Blue Cross Blue Shield (BCBS) is a federation of 35 independent health insurance companies that provide coverage to over 100 million Americans. The organization's national headquarters is located in Chicago, Illinois, while individual BCBS companies operate in various states across the country.

This interview analysis is sponsored by CLARA Analytics and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Explainable AI models are essential in pharmaceutical R&D because they provide transparency and understanding of how AI-driven predictions are made. In drug discovery and development, stakeholders, including researchers, regulatory bodies, and healthcare professionals, need to trust and understand AI models' outputs to make informed decisions. Without explainability, AI models can be seen as "black boxes," leading to skepticism and reluctance to adopt these technologies in critical decision-making processes.