33 stories tagged Medical · page 2 of 2
Researchers found that AI models often give inconsistent answers when presented with conflicting medical information. This highlights a key challenge in using AI for healthcare decisions. (~50 words)
Researchers have developed an AI system called OncoAgent that helps doctors make better cancer treatment decisions without compromising patient privacy. This dual-tier framework uses multiple AI agents to analyze medical data securely.
Researchers have developed a framework to better detect and prevent AI-generated medical misinformation. This could make medical AI tools more reliable for everyday users.
Researchers have developed ClinicBot, an AI chatbot designed for medical professionals that prioritizes accurate, guideline-based answers. Unlike other AI tools, it avoids made-up information and provides verifiable citations for its responses.
Hospitals in China are selling de-identified patient data to tech companies to train AI models. This raises concerns about privacy and data security, despite the data being anonymized.
DeepMind has unveiled an AI co-clinician designed to assist healthcare professionals. This innovation promises to enhance diagnostic accuracy and streamline patient care.
Researchers fine-tuned a vision-language model to generate natural language descriptions of embryo morphology using just 1,000 images. This could standardize IVF assessments and reduce reliance on annotated data.
A new survey and benchmark reveal that while large language models excel at medical exams, their clinical reasoning falls short. The study underscores the need for robust medical reasoning capabilities in real-world healthcare settings.
Researchers created EMSDialog, a dataset of 4,414 synthetic multi-speaker emergency medical dialogues. The dataset is designed to train AI models to track evolving evidence in streaming clinical conversations and make accurate diagnoses.