The benefits of medical AI assistance vary based on user expertise
Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.
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Diagnostics
AI to help researchers see the bigger picture in cell biology
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Read MoreHow to more efficiently study complex treatment interactions
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Read MoreResearchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Read MoreWith AI, researchers predict the location of virtually any protein within a human cell
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
Read MoreStudy shows vision-language models can’t handle queries with negation words
Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.
Read MoreAI model identifies certain breast tumor stages likely to progress to invasive cancer
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
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