How has AI helped in optimising the Quality Assurance process?
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AI has significantly optimized the Quality Assurance (QA) process across various industries. In the field of assisted reproductive technologies (ARTs), AI-driven models have reduced technical variability, improved embryo quality prediction, and highlighted environmental stressors affecting embryo development . In software engineering, AI tools have been utilized for software quality assurance (SQA), enhancing market-oriented approaches and optimizing business processes within QA strategies . Moreover, in end-of-line (EOL) quality assurance for finished components, a fully AI-based quality classification system has automated the process, achieving high accuracy in quality control through Convolutional Neural Networks (CNN) and explainable AI methods . Additionally, AI has been employed in the medical field to detect subtle MRI scanner faults, such as coil element malfunction, with higher accuracy than human radiographers, showcasing the potential of AI methods in supporting traditional QA processes .
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| Papers (5) | Insight |
|---|---|
| AI, specifically neural networks trained with synthetic data, has enhanced MRI QA by accurately detecting coil element malfunctions in patient images, outperforming radiographers and offering real-time monitoring benefits. | |
| AI, specifically Convolutional Neural Networks, automates end-of-line quality assurance by visually inspecting components, achieving up to 98.7% accuracy, reducing manual labor costs, and enabling automatic sorting based on quality. | |
| AI in ART optimizes Quality Assurance by reducing technician variability, enhancing data generation for gametes/embryos, aiding single-sperm selection, enabling accurate morphokinetic evaluation, and predicting embryo quality noninvasively. | |
| AI tools optimize Quality Assurance by providing cost-effective, rapid analysis for software quality, with 64% of organizations using AI to enhance QA strategies, as per the study on software houses in Pakistan. | |
09 Feb 2022 | AI optimizes Quality Assurance by developing digital audit forms, knowledge bases, and document systems. It ensures conformity with standards, aiding in improving higher education quality effectively. |
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