Proficient in AI (75%) or advanced (25%) in using and developing AI for several years. Read more

AI in Healthcare worked alongside Pure Storage on this survey, with Pure offering an educational grant to sponsor the data gathering and report creation. Data collection, tabulation and collation was the responsibility of AI in Healthcare, thus maintaining the anonymity and integrity as promised to the survey base. Read more

AI apps for imaging outnumber all other categories of FDA-approved apps to date. It’s no surprise then that respondents tell us that rad apps top the list of tools they’re using too, namely to enhance breast, chest, cardiovascular imaging, neuroradiology and cardiothoracic imaging. Diagnosis, detection, screening and scheduling are the areas they focus on deploying solutions over the next 18 months. Read more

Standard practice seems to be a blend of commercial AI solutions and teams at healthcare facilities and systems developing their own, with half adopting this strategy. Read more

Improving accuracy, efficiency and workflow are the top benefits leaders see with AI. Next are enhancing the precision of therapy/treatment, identifying deterioration of patient condition, reducing physician burnout, expanding access to care and cost containment. Read more

Healthcare leaders are in full gear in investing in infrastructure—with 45 percent buying this fiscal year. AI is all about the data and it is infrastructure that opens up access and brings speed for bedside and immediate decision-making. Read more

93% of respondents agree AI is absolutely essential, very important or important to their strategy. Read more

The future is now. It’s here. Health systems are hiring data scientists and spending on infrastructure. Read more