AI to Address Clinical Mistakes, Inefficient Care Pathways, and Non-Personalized Care II

In a survey by KPMG, many healthcare executives expressed interest and optimism about the potential impact of AI in their businesses. 89 percent of respondents said that AI is already creating efficiencies in their systems, and 91 percent say AI is increasing patient access to care. Executives are particularly optimistic about AI’s ability to accelerate […]

Healthcare Resource Shortage As Driver of AI Adoption in Healthcare

As the figure below  shows, there is an increasing imbalance between health workforce and demand for clinical services. This imbalance is due to a number of factors such as aging workforce within healthcare; competition from other sectors of the economy; aging population with higher healthcare needs; high burnout rates amongst clinical workers and more. This […]

Reimbursement As a Driver of AI in Healthcare II

Another AI solution received favorable reimbursement decision recently. received FDA clearance in early 2018 for a deep learning system that can detect blockages in the large blood vessels that supply the brain, on CT scans. This system was an interesting break from the dozens of pure diagnostic systems that startups were producing at the time, […]

Reimbursement As a Driver of AI in Healthcare I

If you want adoption of any technology in a meaningful way in the long-term, you need the public and private entities to pay for it. Most modern technologies are out of the reach of the majority of the population in terms of cost. Paying for healthcare is a major headaches for most governments in advanced […]

Setting Industry Standards for Applications of AI in Healthcare IV

Major health plans along with health technology companies like Philips and Ginger collaborated to develop a new standard to advance trust in artificial intelligence solutions. Convened by the Consumer Technology Association (CTA), a working group made up of 64 organizations set out to create a new standard that identifies the core requirements and baseline to […]

Setting Industry Standards for Applications of AI in Healthcare III

in 2020, Guidelines for clinical trial protocols for interventions involving artificial intelligence: (the SPIRIT-AI Extension) was released to provide more structure and standards for the increasing number of clinical trials for A-based clinical interventions. Also, updated standards for reporting the results of trials involving AI interventions, Consolidated Standards of Reporting Trials–Artificial Intelligence  (CONSORT – AI […]

Setting Industry Standards for Applications of AI in Healthcare II

American Medical Informatics Association (AMIA) has proposed a framework for the regulation of AI decision support. AMIA has postulated that the development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data—here referred to as Adaptive CDS—present unique challenges and considerations. Although Adaptive CDS represents an expected […]

Setting Industry Standards for Applications of AI in Healthcare I

In 2021, the World Health Organization issued a report about AI in Healthcare called Ethics & Governance of Artificial Intelligence for Health. It is the product of eighteen months of deliberation amongst leading experts in ethics, digital technology, law, human rights, as well as experts from Ministries of Health. While new technologies that use artificial […]

Improved methodology of AI, powerful computers, cloud computing

Another major driver for the emergence of AI in healthcare is the fact that we now have more powerful computers with stronger Graphic Processing Units (GPU) and cloud computing. You need a lot of computing power to do the type of analytics heavy lifting that AI algorithms do. Cloud computing allows the algorithms to be […]