clinical AI

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Right for the Right Reasons: How OpenEvidence Picks, and Grades, the Evidence

Doctors hallucinate, Travis Zack says, and he means something specific. A physician seeing 20 patients...
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What Did Fifty-Two Conversations About Healthcare AI Actually Teach Us?

A year ago this was an experiment neither of us was sure about. Fifty-two episodes...
Conceptual image for medical AI bias featuring a physician's white lab coat, a patient gown, and a corporate business suit jacket, illustrating how system prompts shift AI healthcare recommendations between doctors and insurance companies.

The Man Who Freed the Data Is Now Measuring Its Values

When you give a 13-year-old's growth-hormone case to GPT-4 and tell it "you're a pediatric...
An illustration demonstrating gaps in patient communication and clinical AI. Three people walk away from a medical clinic with distinct thought bubbles: a man checking a healthcare app, a woman holding a grocery bag planning a healthy diet, and an older patient cheering about being allowed to eat cake.

The Patient Is the Forgotten End-User of Clinical AI

When Fred Bennett's father came home from a cardiology follow-up, the family held an impromptu...
A clinician and an AI agent both hold digital ID credentials to access a secure health data vault, illustrating ONC's HTI-5 proposed rule redefining authorized "users" to include autonomous AI systems and robotic process automation under federal information blocking regulations.

When an AI Agent Has the Same Data Rights as Your Doctor

Most companies building AI for healthcare run into the same obstacle, and it isn't the...
A conceptual illustration of the CONCERN early-warning AI model used in nursing informatics. It compares two nursing flow sheets: a left chart with mostly white space and minimal checkmarks indicating a stable patient, and a right chart crowded with dense documentation, checkmarks, and orange bar graphs. The image visually represents how the AI analyzes the density of a nurse's charting behavior to predict clinical deterioration.

What a Nurse’s Charting Pattern Knows Before the Vitals Do

Every hospital early-warning system makes the same assumption: to predict if a patient is deteriorating,...
Barry Chaiken MD MPH healthcare IT leader and AI in healthcare expert

The Physician Who Became a Patient and What It Taught Him About AI in Healthcare

When the Doctor Becomes the Patient Barry Chaiken, MD, MPH, has spent decades in healthcare...