AIMC Topic: Spectroscopy, Fourier Transform Infrared
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Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.
Scientific reports
Aug 20, 2024
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time...
Artificial intelligence in microplastic detection and pollution control.
Environmental research
Aug 16, 2024
The rising prevalence of microplastics (MPs) in various ecosystems has increased the demand for advanced detection and mitigation strategies. This review examines the integration of artificial intelligence (AI) with environmental science to improve m...
Infrared spectroscopy coupled with machine learning algorithms for predicting the detailed milk mineral profile in dairy cattle.
Food chemistry
Aug 8, 2024
Milk minerals are not only essential components for human health, but they can be informative for milk quality and cow's health. Herein, we investigated the feasibility of Fourier Transformed mid Infrared (FTIR) spectroscopy for the prediction of a d...
Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.
Food chemistry
Aug 2, 2024
Pigmented rice contains beneficial phenolic antioxidants but analysing them across germplasm collections is laborious and time-consuming. Here we utilised rapid surface Fourier transform infrared (FTIR) spectroscopy and machine learning algorithms (M...
Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.
Talanta
Jul 31, 2024
This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients...
Combining spectrum and machine learning algorithms to predict the weathering time of empty puparia of Sarcophaga peregrine (Diptera: Sarcophagidae).
Forensic science international
Jul 14, 2024
The weathering time of empty puparia could be important in predicting the minimum postmortem interval (PMImin). As corpse decomposition progresses to the skeletal stage, empty puparia often remain the sole evidence of fly activity at the scene. In th...
ATR-FTIR spectroscopy and machine/deep learning models for detecting adulteration in coconut water with sugars, sugar alcohols, and artificial sweeteners.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 3, 2024
Packaged coconut water offers various options, from pure to those with added sugars and other additives. While the purity of coconut water is esteemed for its health benefits, its popularity also exposes it to potential adulteration and misrepresenta...
Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening.
Cell reports. Medicine
Jun 28, 2024
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions,...
Identification of geographical origins of Gastrodia elata Blume based on multisource data fusion.
Phytochemical analysis : PCA
Jun 27, 2024
INTRODUCTION: Identifying the geographical origin of Gastrodia elata Blume contributes to the scientific and rational utilization of medicinal materials. In this study, infrared spectroscopy was combined with machine learning algorithms to distinguis...
Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 26, 2024
Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employed as a noninvasive alternative to the standard blood-glucose detection requiring blood-sampling via skin-puncturing, but improving the confidence leve...
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