AIMC Topic: Principal Component Analysis

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Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...

Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in saliva can provide an alternative for drug analysis in forensic toxicology. Therefore, a highly sensitive, fast, reagent-free, and sustainable approach wi...

Predicting maternal risk level using machine learning models.

BMC pregnancy and childbirth
BACKGROUND: Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important ...

Rapid and high accuracy identification of culture medium by CNN of Raman spectra.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Culture media are widely used for biological research and production. It is essential for the growth of microorganisms, cells, or tissues. It includes complex components like carbohydrates, proteins, vitamins, and minerals. The media's consistency is...

A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Journal of food science
Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algori...

Novel concept for the healthy population influencing factors.

Frontiers in public health
In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a p...

Fatal fall from a height: is it possible to apply artificial intelligence techniques for height estimation?

International journal of legal medicine
Fall from a height trauma is characterized by a multiplicity of injuries, related to multiple factors. The height of the fall is the factor that most influences the kinetic energy of the body and appears to be one of the factors that most affects the...

Early colorectal cancer detection: a serum analysis platform combining SERS and machine learning.

Analytical methods : advancing methods and applications
Colorectal cancer (CRC) is one of the deadliest malignancies globally, with high incidence and mortality rates. Early detection is crucial for improving treatment success rates and patient survival. However, due to the difficulty in detecting early s...

Enhancing land cover object classification in hyperspectral imagery through an efficient spectral-spatial feature learning approach.

PloS one
The classification of land cover objects in hyperspectral imagery (HSI) has significantly advanced due to the development of convolutional neural networks (CNNs). However, challenges such as limited training data and high dimensionality negatively im...