AI Articles and Analysis in Healthcare

Athenahealth is a private healthcare company specializing in providing network-powered health services and point-of-care mobile apps. The company’s products and services are designed primarily to enhance patient care, improve operational efficiency and streamline administrative processes.

AI and machine learning have promising potential in the field of healthcare. However, there is one significant hurdle healthcare companies often encounter when trying to implement AI and machine learning. The data architecture of current legacy systems in healthcare settings prevents implementing many use cases and limits a company’s ability to benefit from these technologies fully.

The healthcare industry has experienced several changes in recent decades. The Health Insurance Portability and Accountability Act (HIPAA), signed into law in 1996, represents one such change. HIPAA was initially intended to simplify how healthcare is administered. However, the law also contributed to the increased administrative burden for healthcare practitioners. 

In just the last year, rapid advancements in AI technologies, particularly in natural language processing (NLP), have dramatically impacted virtually every industry. Most recently, large language models (LLMs) have become front and center – driven by the overwhelming popularity of OpenAI's ChatGPT. 

Healthcare is an increasingly complex sector of the global economy, and AI is playing an active role in the worldwide evolution of the industry throughout its many disciplines. In a Deloitte study released earlier this year, 85% of respondents among healthcare business leaders said their enterprise was increasing AI spend before 2023. 

This article was originally written as part of a PDF report sponsored by expert.ai, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

This is a contributed article by Kristóf Zsolt Szalay. Kristóf is Founder and CTO at Turbine.AI, and holds a PhD in molecular biology and bioinformatics. To inquire about contributed articles from outside experts, contact [email protected].

This article is based on a presentation at the 2017 AI Applications Summit conference in Boston, entitled “Artificial Intelligence in the Hospital Setting” (slide deck embedded below) delivered by Emerj CEO Daniel Faggella - updated with recent insights and interviews from Emerj's podcast and AI Opportunity Landscape data.