AI Articles and Analysis in Healthcare

Chatbots are one of the most talked-about uses of natural language processing (NLP) software in business. Some of the most common application areas for chatbots include customer service, healthcare, and financial advisory.

McKesson is a large pharmaceutical distributor that delivers health information technology, medical tools and supplies, and care management tools and software to healthcare providers in the United States. The company has been working to incorporate artificial intelligence solutions internally since 2012, but in more recent years they have adopted a few important automation tools. 

Most people may associate augmented reality (AR) with smartphone apps and video games, perhaps even Pokemon Go. But augmented reality is gaining traction in a variety of industries, including manufacturing and healthcare.

Life sciences companies are likely to begin experimenting further with AI in their workflows in the coming years, but they face challenges in AI adoption due to strict regulations. Machine learning has a "black box" problem, meaning that it's in many cases impossible to know how a machine learning algorithm comes to its conclusions.

Artificial intelligence is changing the way healthcare networks do business and physicians perform their routine activities from medical transcription to robot-assisted surgery. Although the more mature use-cases for AI in healthcare are those built on algorithms that have applications in various other industries (namely white-collar automation), we believe that in the coming three to five years, AI solutions for healthcare will become increasingly specialized to individual use-cases.

There are many possibilities for automation in the healthcare industry outside of AI. Robotic process automation (RPA) technology can serve healthcare companies with various use cases involving data transfer and clinical documentation. Moving important information from the business’ frontend to their deeper business processes is among the most common use cases for RPA in healthcare, and many other solutions emerge from this idea. A similar phrase and field to RPA is called White Collar automation and readers can find a full interview on white collar automation in healthcare today here. 

The healthcare industry holds perhaps the most responsibility of any industry when it comes to ensuring data privacy. A breach in electronic medical records (EMRs) could tarnish a healthcare company's reputation, put undue stress on patients, and render the company in violation of regulations.

Generic pharmaceuticals require less research and development than their brand name counterparts. As a result, AI applications for research and development don’t seem to be the most prominent solutions for generic drug companies. That said, despite the lack of precedence, there may be many areas in which AI could help generic drug companies.