AIMC Topic: Quality Control
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Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review.
The American journal of Chinese medicine
Dec 2, 2021
Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithms. Owing to all research of traditional Chinese medicine (TCM) belonging to the digitalization of cl...
Machine Learning for Health: Algorithm Auditing & Quality Control.
Journal of medical systems
Nov 2, 2021
Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as ex...
Artificial intelligence for quality control of oscillometry measures.
Computers in biology and medicine
Sep 14, 2021
BACKGROUND: The forced oscillation technique (FOT) allows non-invasive lung function testing during quiet breathing even without expert guidance. However, it still relies on an operator for excluding breaths with artefacts such as swallowing, glottis...
An online, non-destructive method for simultaneously detecting chemical, biological, and physical properties of herbal injections using hyperspectral imaging with artificial intelligence.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aug 6, 2021
Botanical drugs hold great potential to prevent and treat complex diseases. Quality control is essential in ensuring the safety, efficacy, and therapeutic consistency of these drug products. The quality of a botanical drug product can be assessed usi...
Quality control stress test for deep learning-based diagnostic model in digital pathology.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jun 24, 2021
Digital pathology provides a possibility for computational analysis of histological slides and automatization of routine pathological tasks. Histological slides are very heterogeneous concerning staining, sections' thickness, and artifacts arising du...
Automated Data Quality Control in FDOPA brain PET Imaging using Deep Learning.
Computer methods and programs in biomedicine
Jun 22, 2021
INTRODUCTION: With biomedical imaging research increasingly using large datasets, it becomes critical to find operator-free methods to quality control the data collected and the associated analysis. Attempts to use artificial intelligence (AI) to per...
U-Net Deep-Learning-Based 3D Cell Counter for the Quality Control of 3D Cell-Based Assays through Seed Cell Measurement.
SLAS technology
Jun 2, 2021
Conventional cell-counting software uses contour or watershed segmentations and focuses on identifying two-dimensional (2D) cells attached on the bottom of plastic plates. Recently developed software has been useful tools for the quality control of 2...
Self-organising maps for the exploration and classification of thin-layer chromatograms.
Talanta
May 13, 2021
Thin-layer chromatography (TLC) allows the swift analysis of larger sample sets in almost any laboratory. The obtained chromatograms are patterns of coloured zones that are conveniently evaluated and classified by visual inspection. This manual appro...
Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.
Stem cells (Dayton, Ohio)
Mar 30, 2021
Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop quality control methods to standardize stem cell manufacturing. Here, we report a deep learning-based automated cell tracking (DeepACT) technology fo...
Automating chest radiograph imaging quality control.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Mar 23, 2021
PURPOSE: To automate diagnostic chest radiograph imaging quality control (lung inclusion at all four edges, patient rotation, and correct inspiration) using convolutional neural network models.
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