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Traumatizing AI models by talking about war or violence makes them more anxious

A recent study exposing AI models to carefully designed prompts around trauma revealed they can get anxious, potentially affecting the conversation and having negative impacts on people who use such models to discuss their mental health.

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AI meets oncology: New model personalizes bladder cancer treatment

Leveraging the power of AI and machine learning technologies, researchers at Weill Cornell Medicine developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy.

Artificial intelligence is already being used in your health care. What to know

The use of AI applications in medical care is growing. Dr. Leana Wen explains the uses of AI that could improve care — and the reasons for continued caution.

Apple's AI isn't a letdown. AI is the letdown

Apple has been getting hammered in tech and financial media for its uncharacteristically messy foray into artificial intelligence. After a June event heralding a new AI-powered Siri, the company has delayed its release indefinitely.

AI-Based Histologic Assays Identify BCG-Unresponsive Signature in NMIBC Cases

Investigators employed artificial intelligence to characterize tissue samples of high-risk NMIBC that were likely to recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG).

AI Translates Retail Jargon Into Shopper-Friendly Content

In an age where AI has transformed nearly every industry, retailers need to harness its potential to bridge the gap between merchant speak or industry jargon and consumer dialect.

AI Guides Nonexperts to Expert-Level Lung Ultrasound

AI assistance enabled trained HCPs with minimal lung ultrasound experience to capture images that met diagnostic standards, which were comparable with those captured by experts.

AI in healthcare may be making unfair decisions: Study unveils alarming bias

The study introduces G-AUDIT (Generalized Attribute Utility and Detectability-Induced bias Testing) as a data modality-agnostic auditing tool, meaning it can be applied across different types of medical datasets,