AIMC Topic: Spectrum Analysis, Raman

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Direct estimation of amylose and amylopectin in single starch granules by machine learning assisted Raman spectroscopy.

Carbohydrate polymers
Starch is a fundamental carbohydrate with nutritional and physicochemical properties governed by relative proportions of amylose and amylopectin. Variations in amylose-to-amylopectin ratio significantly influence starch digestibility, texture, glycem...

Study on the quantitative analysis of Tilianin based on Raman spectroscopy combined with deep learning.

PloS one
Tilianin is a commonly used pharmaceutical ingredient with various biological activities such as antioxidant, anti-inflammatory, and anticancer, which is able to exert antitumor effects by inhibiting tumor cell proliferation, inducing apoptosis and i...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Analytical chemistry
Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current clinical diagnosis relies on endoscopic biopsy and histopathological analysis, which are highly depende...

Data-Augmented Deep Learning Algorithm for Accurate Control of Bioethanol Fermentation Using an Online Raman Analyzer.

Biotechnology and bioengineering
Fed-batch fermentation has become the preferred strategy in many industrial biomanufacturing processes. However, a key challenge remains in optimizing the feeding strategy to achieve stable maximum yields. In this study, we present an online Raman sp...

Preoperative Identification of Papillary Thyroid Carcinoma Subtypes and Lymph Node Metastasis via Deep Learning-Assisted Surface-Enhanced Raman Spectroscopy.

ACS nano
Accurate preoperative diagnosis of papillary thyroid carcinoma (PTC) histological subtypes and lymph node metastasis is essential for formulating personalized treatment strategies. However, their preoperative diagnosis is challenged by the limited re...

Shining Light on DNA Mutations through Machine Learning-Augmented Vibrational Spectroscopy.

Analytical chemistry
A method to directly predict the number of nucleic acid bases in a single-stranded DNA (ssDNA) or a genomic DNA has been proposed with a combination of Raman spectroscopy and an Artificial Neural Network (ANN) algorithm. In this work, the algorithm w...

Machine learning-enhanced SERS diagnostics: Accelerating the AI-powered transition from laboratory discoveries to clinical practice.

Computers in biology and medicine
Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative analytical tool in disease diagnostics, offering unparalleled sensitivity and molecular fingerprinting capabilities. However, its clinical translation is hindered by the inher...

Measuring alignment of structural proteins in engineered tissue constructs using polarized Raman spectroscopy.

PloS one
Measures of structural protein alignment within biological and engineered tissues are needed for improved understanding of their mechanical behavior and functionality. We advance our method of measuring protein alignment using polarized Raman spectro...