100 stories tagged Healthcare · page 2 of 5
China is set to launch its first AI-powered cancer vaccine production line in Beijing. The facility uses artificial intelligence to optimize and accelerate vaccine development and production, promising faster, more precise, and personalized cancer treatments.
Researchers developed an AI system that combines official drug data with patient experiences to provide safer, more accurate medication information. This could help people make better decisions about their mental health treatments.
AI systems are now authorized to prescribe medications independently in the U.S. This shift raises critical questions about trust, liability, and how to handle uncertainty in medical decisions. Researchers highlight gaps in current regulations that could impact patient safety.
A new study found that AI chatbots fail to provide consistent safety for most mental health conditions. Only suicide and self-harm have reliable safeguards in place. Researchers call for better standards and transparency.
AI is having an 'Uber moment' in healthcare, becoming as essential as smartphones in hospitals. It's helping doctors diagnose diseases faster and more accurately, potentially making care more accessible and affordable.
Researchers found that large language models (LLMs) often overestimate their confidence when analyzing medical data. The study suggests new methods to help AI recognize what it doesn't know, improving reliability in healthcare applications.
Researchers developed an AI tool called ACIE that better handles complex medical records. It addresses key challenges in retrieving and understanding patient data across multiple documents. This could lead to more accurate and efficient medical diagnoses and treatments.
Researchers developed REVEAL++, an AI method that analyzes retinal fundus images and structured clinical narratives to predict Alzheimer's disease risk. The approach improves upon prior work by introducing differentiable phenotypic grouping for more precise risk stratification.
Researchers have developed a machine-learned comorbidity index that better predicts patient outcomes. Unlike older methods, it captures complex relationships between diseases and health risks.
Midjourney CEO David Holz just showed off the company's first hardware product and plans to build a San Francisco spa. Dubbed The Midjourney Scanner, it's an ultrasound-based full-body scanner that uses a ring of sensors to capture vertical images of the body.
Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases. This could revolutionize how doctors approach these complex conditions.
Pramaana Labs has secured $27 million to develop AI systems that can be formally verified for accuracy. This technology aims to eliminate errors in fields like law and drug discovery where mistakes can be costly.
Researchers created SpeechDx, a comprehensive benchmark for AI to analyze speech for health conditions. This tool could lead to earlier, more accurate medical diagnoses through simple voice recordings.
Google's AMIE AI system can now manage complex health conditions as well as primary care physicians. This breakthrough could make high-quality medical advice more accessible to everyone.
Researchers developed an AI system that creates digital twins of patients to simulate treatments and optimize care in real-time while adhering to safety constraints. This approach could lead to more personalized and effective medical decisions.
Researchers introduced ReportQA, a new AI system that evaluates radiology reports by asking and answering clinically relevant questions. Unlike traditional metrics, ReportQA mimics how doctors use reports for diagnosis, potentially improving the quality and usefulness of AI-generated medical reports.
Researchers have developed a way to simplify deep learning models for EEG analysis, making them more practical for wearable devices. This could lead to more affordable and accessible brain-monitoring technology for everyday use.
Researchers developed a method to predict when AI assistants in healthcare might fail. This could make clinical AI tools safer and more reliable for doctors and patients. The study analyzed real-world use of AI in electronic health records to identify risky responses before they happen.
Researchers created a benchmark to test AI's ability to synthesize scientific conclusions. This could improve AI decision-making in critical areas like healthcare.
A study found that teaching AI models to explain their predictions actually makes them worse at diagnosing Alzheimer's disease and related dementias. This challenges the common belief that reasoning abilities improve AI performance in healthcare.
Researchers developed PathoSage, an AI system designed to improve medical diagnoses by reducing errors in analyzing tissue samples. It separates knowledge gathering from decision-making to avoid conflicting evidence.
Researchers developed an AI system that predicts knee pain from MRI scans with high accuracy. The framework combines deep learning and statistical modeling to make the results interpretable and trustworthy.
Researchers created ChatHealthAI to combine AI's language skills with medical records. This could help doctors make better decisions using patient history. The system is still in early development, but it shows promise for improving healthcare.
Researchers created a multi-domain red teaming framework to evaluate how well AI models handle complex medical scenarios. The study found significant gaps in safety and fairness across 11 leading AI models.