AIMC Topic: Spectrum Analysis, Raman

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Advanced SERSome-based artificial-intelligence technology for identifying medicinal and edible homologs.

Talanta
Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control and rapid ...

Comprehensive Raman spectroscopy analysis for differentiating toxic cyanobacteria through multichannel 1D-CNNs and SHAP-based explainability.

Talanta
Cyanobacterial blooms pose significant environmental and public health risks due to the production of toxins that contaminate water sources and disrupt aquatic ecosystems. Rapid and accurate identification of cyanobacterial species is crucial for eff...

Digital Butterworth filter as preprocessing method for implementing Raman spectroscopy as an analytical method in downstream processing of biopharmaceuticals.

Journal of chromatography. A
For implementing Raman spectroscopy as an analytical method in downstream processing, extracting molecular information related to biopharmaceuticals is still challenging due to spectral variations caused by spectrometer, setup and fluorescence. This ...

Paper-based SERS chip with adaptive attention neural network for pathogen identification.

Journal of hazardous materials
High-speed and accuracy identification of pathogens has become increasingly critical in both individual patient care and public health. Artificial intelligence (AI)-assisted surface-enhanced Raman scattering (SERS) biosensors enable simultaneous iden...

The emerging role of artificial intelligence applied to exosome analysis: from cancer biology to other biomedical fields.

Life sciences
In recent years, exosomes versatility has prompted their study in the biomedical field for diagnostic, prognostic, and therapeutic applications. Exosomes are bi-lipid small extracellular vesicles (30-150 nm) secreted by various cell types, containing...

Reconstructing Super-Resolution Raman Spectral Image Using a Generative Adversarial Network-Based Algorithm.

Analytical chemistry
Raman imaging utilizes molecular fingerprint information to visualize the spatial distribution of a substance within the scanned area. Subject to its scanning mechanism, it usually costs a prolonged data acquisition duration for achieving high-resolu...

Sensitive Detection and Identification Method of Erythrocyte-like Cells upon Doxorubicin Induced Differentiation with Vibrational Techniques.

Analytical chemistry
Altered differentiation of blood cell precursors and their clonal expansion occurs in various types of leukemia. One treatment strategy is to induce differentiation into the mature form, which is capable of undergoing apoptosis. It has been found tha...

Vibrational spectroscopy of body fluids combined with machine learning for the early diagnosis of cystic echinococcosis.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Cystic echinococcosis (CE) is a globally prevalent zoonotic parasitic disease. Due to the covert symptoms and the inadequacies of screening technologies, accurate early diagnosis is crucial. This study explores the feasibility of employing body fluid...

Fusion of near-infrared and Raman spectroscopy with machine learning strategies: Non-destructive rapid assessment of freshness and TVB-N value prediction in Pacific white shrimp (Litopenaeus vannamei).

Food research international (Ottawa, Ont.)
Total volatile base nitrogen (TVB-N) is a key indicator of shrimp freshness. Nevertheless, traditional detection methods are cumbersome, time-intensive, and destructive. Here, a rapid and non-destructive method based on near-infrared (NIR) and Raman ...

Differentiation of Healthy Ex Vivo Bovine Tissues Using Raman Spectroscopy and Interpretable Machine Learning.

Lasers in surgery and medicine
OBJECTIVES: Integrating machine learning with Raman spectroscopy (RS) shows strong potential for intraoperative guidance in orthopedic procedures, but limited algorithm transparency remains a barrier to clinician trust. This study aims to develop int...