AIMC Topic: Quality Control

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Non-destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review.

Comprehensive reviews in food science and food safety
The egg is considered one of the best sources of dietary protein, and has an important role in human growth and development. With the increase in the world's population, per capita egg consumption is also increasing. Ground-breaking technological dev...

Node-Loss Detection Methods for CZ Silicon Single Crystal Based on Multimodal Data Fusion.

Sensors (Basel, Switzerland)
Monocrystalline silicon is an important raw material in the semiconductor and photovoltaic industries. In the Czochralski (CZ) method of growing monocrystalline silicon, various factors may cause node loss and lead to the failure of crystal growth. C...

An AI-Based Image Quality Control Framework for Knee Radiographs.

Journal of digital imaging
Image quality control (QC) is crucial for the accurate diagnosis of knee diseases using radiographs. However, the manual QC process is subjective, labor intensive, and time-consuming. In this study, we aimed to develop an artificial intelligence (AI)...

Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review.

Critical reviews in analytical chemistry
Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of crucial importance. In recent years, with the quick rise of artificial intelligence (AI) and the rapid development of hyperspectral imaging (HSI) techno...

Quality control system for mammographic breast positioning using deep learning.

Scientific reports
This study proposes a deep convolutional neural network (DCNN) classification for the quality control and validation of breast positioning criteria in mammography. A total of 1631 mediolateral oblique mammographic views were collected from an open da...

Application of an AI image analysis and classification approach to characterise dissolution and precipitation events in the flow through apparatus.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Imaging and artificial intelligence (AI) approaches have been used with increasing frequency in pharmaceutical industry in recent years. Characterisation of processes such as drug dissolution and precipitation is vital in quality control testing and ...

Digital by design approach to develop a universal deep learning AI architecture for automatic chromatographic peak integration.

Biotechnology and bioengineering
Chromatographic data processing has garnered attention due to multiple Food and Drug Administration 483 citations and warning letters, highlighting the need for a robust technological solution. The healthcare industry has the potential to greatly ben...

Quality assessment of traditional Chinese medicine based on data fusion combined with machine learning: A review.

Critical reviews in analytical chemistry
The authenticity and quality of traditional Chinese medicine (TCM) directly impact clinical efficacy and safety. Quality assessment of traditional Chinese medicine (QATCM) is a global concern due to increased demand and shortage of resources. Recentl...

Improving quality control in the routine practice for histopathological interpretation of gastrointestinal endoscopic biopsies using artificial intelligence.

PloS one
BACKGROUND: Colorectal and gastric cancer are major causes of cancer-related deaths. In Korea, gastrointestinal (GI) endoscopic biopsy specimens account for a high percentage of histopathologic examinations. Lack of a sufficient pathologist workforce...

Convolutional neural network -based phantom image scoring for mammography quality control.

BMC medical imaging
BACKGROUND: Visual evaluation of phantom images is an important, but time-consuming part of mammography quality control (QC). Consistent scoring of phantom images over the device's lifetime is highly desirable. Recently, convolutional neural networks...