Artificial Intelligence

Chief Data and AI Officer Mouneer Odeh says work on artificial intelligence is like a snowball going downhill – over the next five to 10 years it will build and build until the scale of the impact meets what healthcare requires.

Also: Three partners will combine advanced analytics, social risk assessments and actuarial validation to measure the impacts of SDOH interventions.

At Cedars-Sinai Medical Center, artificial intelligence extracts important information from data that can help inform care or drive operational efficiencies, says Kathy Bailey, the health system's principal data intelligence analyst.

Healthcare needs its workforce to be skilled in AI, says Bob Dichter, founder and career coach at Phoenix Rising Career Services, who encourages IT professionals to use artificial intelligence tools to help solve their organizations' challenges.

Join us for an enlightening webinar that explores the transformative power of AI and automation in healthcare. Discover how these cutting-edge technologies are not only streamlining operations but also making healthcare more personal and humane. Learn from our industry experts how AI is reducing burnout and improving the overall well-being of healthcare providers, leading to a more efficient care environment.

Ethical and equitable use of open data is a critical challenge for AI development in healthcare, requiring global collaboration to balance innovation with privacy and security, says Antoine Tesnière, professor at George Pompidou European Hospital.  

With its Nursing Research and Innovation Council fostering the use of digital tools and the hospital training staff in employing artificial intelligence, it is improving tech adoption, says Debra Beauregard of Rady Children's Health.

A digital health literacy maturity model could aid in training and inspiring staff to adopt new tools and cybersecurity practices, says Tjasa Zajc, special advisor for HIMSS and moderator for the HIMSS25 Global Leaders Exchange panel.

The University of California at San Francisco's overarching goal was not to replace human judgment but to enhance it – allowing oncologists to focus on personalized treatment rather than spending valuable time retrieving and verifying information.

Almost 20% of healthcare workers polled recently said they spend more than 20 hours per month correcting billing errors. Artificial intelligence can help, but adding automation to billing systems is no easy task.