AI & ML Intelligence

Artificial intelligence is becoming so user-friendly that doctors can code custom clinical workflow tools. But AI-driven vulnerability discovery is fast reshaping cybersecurity imperatives for IT leaders.

As artificial intelligence tools become more integrated and routine in care delivery, new enforcements could focus on governance, documentation and oversight, one healthcare attorney says. He offers his thoughts on defense strategies in healthcare AI-related cases.

Clinicians using one vendor's algorithm found lung squamous cell carcinoma misdiagnoses, influencing treatment decisions and patient outcomes. The company's chief clinical officer walks through the JAMA study.

The health system has a three-pronged strategy: leveraging pre-built tools, maximizing robotic process automation for efficiency and deploying LLMs to provide human-level reasoning across its operations.

The challenge is not in using artificial intelligence but ensuring the technology is implemented responsibly, in ways that truly benefit patients and providers, says Darrell Bodnar of North Country Healthcare.

Aaron Wootton, chief information officer at Stormont Vail Health, says artificial intelligence deployments not grounded in clearly defined outcomes create short-term enthusiasm – but rarely deliver sustainable value.

At Dermatology Partners, 25% of AI-routed calls are resolved through appointment-related tasks. Staff are optimistic about clinical task workflow – their near-term goal is to exceed a 50% AI resolution rate.

For every provider who switches from virtual human scribes to AI ambient voice scribes, the 100-provider Seattle group practice saves about $2,000 per month. And there's more, as one of the pediatricians details.

The independent health system's new tech saves time on the scanning side while aiding physicians with better views of diagnostic images. The CIO discusses the benefits of this powerful system.

A top AI researcher at Harvard's Beth Israel Deaconess Medical Center describes the good and the bad of patients' increasing use of large language models to research their health. Health systems must embrace this new trend, he says.