Highlights from the SIIM annual meeting focus on AI in radiology, advanced imaging trends, and innovations in report quality.
Key Details
- 1SIIM annual meeting featured major discussions on AI, informatics, and future radiology trends.
- 2LLMs are being researched for boosting error detection in x-ray reports.
- 3Debates included whether foundation models will shape the future of radiology AI.
- 4Presentations explored AI's impact on radiology workload and sustainability.
- 5Studies showcased advances like CT identifying increased malignancy risk and FAPI-SPECT/CT in GI cancer diagnosis.
Why It Matters
This round-up covers leading developments in radiology AI, revealing how advanced informatics and automation like LLMs are poised to influence diagnostic accuracy, workflow, and patient care. For radiology professionals, understanding these trends is crucial for navigating upcoming changes in AI, regulation, and practice management.
Source
AuntMinnie
Related News
•AuntMinnie
Habitat AI Model Improves Risk Stratification of Lung Nodules on LDCT
A 'habitat' AI model outperforms standard 2D approaches in stratifying lung adenocarcinoma risk in subsolid nodules on low-dose CT scans.
•Cardiovascular Business
Former US Surgeon General Jerome Adams Joins Eko as Medical Advisor
Former US Surgeon General Jerome Adams has joined Eko Health as a distinguished medical advisor to support AI-powered cardiac and pulmonary detection technologies.
•AuntMinnie
AI Model Uses Chest CT to Diagnose and Grade COPD Severity
A machine learning model based on chest CT images accurately diagnoses and grades the severity of COPD.