FDA Grants Breakthrough Status to AI for Radiology Report Drafting
The technology analyzes chest radiographs to generate preliminary report text, aiming to address increasing imaging volumes and interpretation delays.
Category: Cloud Computing
Cloud Computing
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Cloud Computing
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AI Tool Cleared to Help Detect Lung Nodules and Triage Chest Emergencies
New FDA clearances authorize the use of an AI tool to detect lung nodules and help triage pneumothorax and pleural effusion on chest X-rays.
Cloud Computing
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AI Can Improve Ovarian Cancer Diagnoses
A study published in Nature Medicine shows that Swedish researchers developed AI models that outperformed human experts in detecting ovarian cancer from ultrasound images, offering improved diagnostic accuracy and reduced need for expert referrals.
Deep Learning Model Enhances Knee MRI Diagnostics
A Hong Kong-based team has developed the Co-Plane Attention across MRI Sequences deep learning model to classify 12 knee abnormalities from multi-sequence MRI, improving diagnostic accuracy, efficiency, and aligning with clinical standards while bridging expertise gaps in radiology.
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ACR Launches AI Quality Registry
The American College of Radiology (ACR) has launched Assess-AI, the first AI quality registry to monitor and analyze the real-world performance of imaging AI algorithms, providing radiology facilities with performance insights, national benchmarks, and tools to ensure safe, effective, and transparent AI integration in clinical practice.
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How AI Is Addressing Unique Challenges in Radiology
In this exclusive interview, Avez Rizvi, MD, CEO of RADPAIR, shares insights into the future of AI in radiology and the role RADPAIR aims to play in creating an AI-driven, patient-focused healthcare environment.
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Google Cloud Report: Gen AI to Revolutionize Radiology
Google Cloud’s new report highlights how generative AI can reduce administrative burdens for radiologists by automating documentation and image analysis, improving efficiency, diagnostic accuracy, and patient care quality.
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Enhancing MRI with AI to Improve Diagnosis of Brain Disorders
University of California, San Francisco researchers developed a machine learning algorithm that enhances 3T MRI images to simulate 7T resolution, improving the detection of brain abnormalities like those in traumatic brain injury and multiple sclerosis.
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