37 stories tagged Medical
Researchers propose MA-RAG, a multi-agent retrieval-augmented generation framework that improves the factual accuracy and temporal consistency of AI-generated summaries for longitudinal Parkinson's disease clinical assessments.
Google Research's AMIE AI system successfully demonstrated real-time clinical video consultations in a simulated setting, marking a significant step toward AI-assisted medical consultations.
Researchers developed GuideSkill, an AI system that translates clinical practice guidelines into executable functions to improve diagnostic accuracy. The system can refine its skills over time using real case data, offering a more precise approach to medical decision-making.
NVIDIA released Cosmos-H-Dreams, an open-source generative simulation tool that lets surgical robots practice complex procedures in real-time virtual environments, improving safety and precision before they ever touch a patient.
OpenAI launched Health in ChatGPT, enabling eligible U.S. users to securely link their medical records and Apple Health data. The feature delivers personalized health insights and helps users better understand their health.
Researchers introduced GraphDx, a multi-agent AI framework that uses a Medical Diagnosis Knowledge Graph to balance diagnostic accuracy with resource costs, reducing unnecessary testing in sequential medical diagnosis.
A new arXiv study proposes converting all patient data—clinical narratives, vital signs, lab values, and comorbidities—into a single natural language sequence and fine-tuning a pretrained LLM, eliminating the need for task-specific fusion architectures in clinical prediction.
Researchers created CANDI-QA, a new test for AI models to evaluate their ability to answer complex questions in specialized fields like medicine and finance. This helps ensure AI assistants can provide accurate, context-aware answers in critical areas.
Researchers developed a new AI system that explains medical diagnoses using a structured argumentation model. This approach makes AI recommendations more transparent and trustworthy for doctors.
Researchers created MedRealMM, a real-world benchmark for medical AI that includes real patient-doctor conversations and medical images. This could lead to more accurate and reliable AI tools for online healthcare consultations.
A new research paper outlines how large language models (LLMs) are being used in healthcare, bridging the gap between clinical needs and AI capabilities. The study proposes a framework to align medical training standards with AI's potential in patient care.
Researchers developed a new AI approach that mimics how doctors gather evidence to make diagnoses. This method could make AI medical tools more accurate and reliable.
Midjourney unveiled its dunk-tank ultrasound scanner, aiming to revolutionize medical imaging. However, the company has yet to provide concrete proof that the technology works as advertised.
Researchers created a dataset of 240 French doctor-patient conversations to train AI virtual patients. This could make medical training more accessible and effective for students worldwide.
Midjourney, known for AI-generated images, is now developing a futuristic ultrasound scanner that dunks users in a vat of water. Experts question the feasibility and evidence behind this sudden shift.
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 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.
OpenAI has upgraded ChatGPT's health intelligence with GPT-5.5 Instant, making its medical advice more accurate and reliable. This update includes stronger reasoning, better context, and evaluations by physicians.
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.
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 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 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.