AIMC Topic: Quality Control

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Quality Control in the Corneal Bank with Artificial Intelligence: Comparison of a New Deep Learning-based Approach with Conventional Endothelial Cell Counting by the "Rhine-Tec Endothelial Analysis System".

Klinische Monatsblatter fur Augenheilkunde
Endothelial cell density (ECD) is a crucial parameter for the release of corneal grafts for transplantation. The Lions Eye Bank of Baden-Württemberg uses the "Rhine-Tec Endothelial Analysis System" for ECD quantification, which is based on a fixed co...

Improving newborn screening in India: Disease gaps and quality control.

Clinica chimica acta; international journal of clinical chemistry
In India, newborn screening (NBS) is essential for detecting health problems in infants. Despite significant progress, significant gaps and challenges persist. India has made great strides in genomics dueto the existence of the National Institute of ...

Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

Journal of clinical laboratory analysis
BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained attention because of its potential to continuously monitor the analytical quality in situations wherein internal quality control (IQC) is less effective. Therefore, we tried to i...

Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective.

Molecules (Basel, Switzerland)
Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objecti...

Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substand...

Machine learning-based nonlinear regression-adjusted real-time quality control modeling: a multi-center study.

Clinical chemistry and laboratory medicine
OBJECTIVES: Patient-based real-time quality control (PBRTQC), a laboratory tool for monitoring the performance of the testing process, has gained increasing attention in recent years. It has been questioned for its generalizability among analytes, in...

Identification of growth years for Puerariae Thomsonii Radix based on hyperspectral imaging technology and deep learning algorithm.

Scientific reports
Puerariae Thomsonii Radix (PTR) is not only widely used in disease prevention and treatment but is also an important raw material as a source of starch and other food. The growth years of PTR are closely related to its quality. The rapid and nondestr...

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)...