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Artificial Intelligence

Micky Tripathi, former HHS acting chief AI officer
By Andrea Fox | |
Micky Tripathi, who also served as acting chief artificial intelligence officer at HHS, is said to be in line for the new chief AI implementation officer role at the Minnesota healthcare innovator.
A doctor reviewing a patient's chart
By Adam Ang | |
Northern Health in Melbourne has replaced its legacy system with AI-assisted coding.
Manipal Hospitals branch in Old Airport Road, Bangalore, India
By Adam Ang | |
Pharmacy order processing was brought down to under five minutes.
Healthcare worker pointing at x-ray image on monitor
By Anthony Vecchione | |
A study published in the European Journal of Cancer says inaccurate results and misdiagnoses could occur if diverse populations are not included in clinical research.
Mouneer Odeh of Cedars-Sinai on Chief AI Officers
By Bill Siwicki | |
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.
Hospital doctors meeting
By Andrea Fox | |
Also: Three partners will combine advanced analytics, social risk assessments and actuarial validation to measure the impacts of SDOH interventions.
Dr. Travis Zack of the University of California at San Francisco on AI
By Bill Siwicki | |
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.
Healthcare billing office worker makes a correction
By Nathan Eddy | |
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.
By Andrea Fox | |
Its newest report tracking rates of artificial intelligence adoption shows significant maturity in large acute care providers. Key use cases include clinical decision support, documentation automation and workflow efficiency.
Matthew Temba of Strive Health on machine learning
By Bill Siwicki | |
The kidney care provider's build-not-buy effort has shown great results: 30-day readmissions are down 36%, hospitalizations among high-risk patients are down 49% and optimal starts are up 67%.