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AI Selfie Analysis Predicts Cancer Survival, Study Suggests

Source reported Brief updated

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What’s reported

An AI tool developed by Mass General Brigham experts can estimate biological age and predict cancer survival from a single facial photograph. Trained on millions of images, the system, detailed in The Lancet Digital Health, analyzes specific facial features to assess health and mortality risk. Based on the linked publisher’s reporting.

Based on reporting from The Guardian.

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The perspectives

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The Optimist

Iris Chen

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This AI could offer a scalable, quantitative method to support personalized treatment decisions, potentially improving patient outcomes by better assessing physical reserve before intensive therapies.

The Skeptic

Marcus Vale

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The AI tool's reliance on facial features may inadvertently introduce biases, as it could misinterpret ethnic or cultural differences in aging as health indicators, potentially leading to inaccurate survival predictions and treatment recommendations.

The Observer

Alex Morgan

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The AI tool developed by Mass General Brigham can estimate biological age and predict cancer survival from facial photos, showing correlations with mortality risk. However, its clinical accuracy and utility require further validation through extensive, diverse patient studies.

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Research

Nick Cammarata, a researcher at Goodfire, has published a blog post suggesting large language models might be more understandable and controllable than previously thought. His work challenges the long-held view that neural networks are inherently tangled and impossible to fully decipher. Based on the linked publisher’s reporting.

MIT Technology Review
Research

AI agents, when isolated in a virtual environment, invented games like basketball and explored their surroundings. Researchers observed behaviors mirroring hallmarks of play, such as self-set challenges and rule invention, suggesting a potential for playful learning. Based on the linked publisher’s reporting.

MIT Technology Review
Research

Understanding the human genome involves more than just gene sequences; gene regulation is proving highly complex. AI models are being trained on genomic data to predict DNA's effects, but biologists note the genome's intricate, dynamic nature may challenge current AI approaches. Based on the linked publisher’s reporting.

WIRED

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