AIMC Topic: Quality Control
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An quality evaluation method based on three-dimensional integration and machine learning: Advanced data processing.
Journal of chromatography. A
Feb 28, 2025
This study presents an innovative approach for the quality evaluation of traditional Chinese medicine (TCM) by integrating three-dimensional (3D) data processing with machine learning, aimed at enhancing the efficiency and accuracy of HPLC-DAD data a...
A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.
Food research international (Ottawa, Ont.)
Feb 15, 2025
With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an eme...
Monitoring Immunohistochemical Staining Variations Using Artificial Intelligence on Standardized Controls.
Laboratory investigation; a journal of technical methods and pathology
Feb 12, 2025
Quality control of immunohistochemistry (IHC) slides is crucial to ascertain accurate patient management. Visual assessment is the most commonly used method to assess the quality of IHC slides from patient samples in daily pathology routines. Control...
A deep learning-based peer review method for radiotherapy planning.
Medical physics
Feb 11, 2025
BACKGROUND: Quality control (QC) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Traditionally, QC relies on standard indicators and subjective assessments, which may lead to inconsistencies.
Integrating hyperspectrograms with class modeling techniques for the construction of an effective expert system: Quality control of pharmaceutical tablets based on near-infrared hyperspectral imaging.
Journal of pharmaceutical and biomedical analysis
Jan 26, 2025
Near-infrared hyperspectral imaging (NIR-HSI) integrated with expert systems can support the monitoring of active pharmaceutical ingredients (APIs) and provide effective quality control of tablet formulations. However, existing quality control method...
iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control.
Nature communications
Jan 21, 2025
Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files fro...
Efficient and accurate commissioning and quality assurance of radiosurgery beam via prior-embedded implicit neural representation learning.
Medical physics
Jan 15, 2025
BACKGROUND: Dosimetric commissioning and quality assurance (QA) for linear accelerators (LINACs) present a significant challenge for clinical physicists due to the high measurement workload and stringent precision standards. This challenge is exacerb...
Novel approach for quality control testing of medical displays using deep learning technology.
Biomedical physics & engineering express
Jan 15, 2025
In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of me...
A deep learning approach to perform defect classification of freeze-dried product.
International journal of pharmaceutics
Jan 3, 2025
Cosmetic inspection of freeze-dried products is an important part of the post-manufacturing quality control process. Traditionally done by human visual inspection, this method poses typical challenges and shortcomings that can be addressed with innov...
Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Dec 22, 2024
Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This st...
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