AIMC Topic: Quality Assurance, Health Care

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Quality Assessment of Brain MRI Defacing Using Machine Learning.

Studies in health technology and informatics
Defacing of brain magnetic resonance imaging (MRI) scans is a crucial process in medical imaging research aimed at preserving patient privacy while maintaining data integrity. However, existing defacing algorithms are prone to errors, potentially com...

INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support.

Studies in health technology and informatics
Digital health solutions hold promise for enhancing healthcare delivery and patient outcomes, primarily driven by advancements such as machine learning, artificial intelligence, and data science, which enable the development of integrated care system...

Applications of artificial intelligence for machine- and patient-specific quality assurance in radiation therapy: current status and future directions.

Journal of radiation research
Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, especially in high-precision radiotherapy such as intensity-modulated radiation therapy (IMRT) and vo...

A Nationwide Network of Health AI Assurance Laboratories.

JAMA
IMPORTANCE: Given the importance of rigorous development and evaluation standards needed of artificial intelligence (AI) models used in health care, nationwide accepted procedures to provide assurance that the use of AI is fair, appropriate, valid, e...

Development of a deep learning-based error detection system without error dose maps in the patient-specific quality assurance of volumetric modulated arc therapy.

Journal of radiation research
To detect errors in patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), we proposed an error detection method based on dose distribution analysis using unsupervised deep learning approach and analyzed 161 prostate VMA...

Deep Learning for Patient-Specific Quality Assurance: Predicting Gamma Passing Rates for IMRT Based on Delivery Fluence Informed by log Files.

Technology in cancer research & treatment
In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation therapy (IMRT) quality assurance (QA) gamma passing rates using delivery fluence informed by log files. A total of 112 IMRT plans for chest cancers we...

Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning.

Medicine
The quality control of fetal sonographic (FS) images is essential for the correct biometric measurements and fetal anomaly diagnosis. However, quality control requires professional sonographers to perform and is often labor-intensive. To solve this p...