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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A review of artificial intelligence methods combined with Raman spectroscopy to identify the composition of substances
Liangrui Pan, Peng Zhang, Chalongrat Daengngam, et al.
Journal of Raman Spectroscopy (2021) Vol. 53, Iss. 1, pp. 6-19
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Recent Progresses in Machine Learning Assisted Raman Spectroscopy
Yaping Qi, Dan Hu, Yucheng Jiang, et al.
Advanced Optical Materials (2023) Vol. 11, Iss. 14
Open Access | Times Cited: 98
Spectroscopic food adulteration detection using machine learning: Current challenges and future prospects
Rishabh Goyal, Poonam Singha, Sushil Kumar Singh
Trends in Food Science & Technology (2024) Vol. 146, pp. 104377-104377
Closed Access | Times Cited: 43
AI in analytical chemistry: Advancements, challenges, and future directions
Rafael Cardoso Rial
Talanta (2024) Vol. 274, pp. 125949-125949
Closed Access | Times Cited: 27
Surface-Enhanced Raman Spectroscopy for Biomedical Applications: Recent Advances and Future Challenges
Li Lin, Ramón A. Álvarez‐Puebla, Luis M. Liz‐Marzán, et al.
ACS Applied Materials & Interfaces (2025)
Closed Access | Times Cited: 3
A Conceptual Overview of Surface-Enhanced Raman Scattering (SERS)
Mina Magdy
Plasmonics (2023) Vol. 18, Iss. 2, pp. 803-809
Closed Access | Times Cited: 26
Machine Learning-Assisted Raman Spectroscopy and SERS for Bacterial Pathogen Detection: Clinical, Food Safety, and Environmental Applications
Md Hasan-Ur Rahman, Rabbi Sikder, Manoj Tripathi, et al.
Chemosensors (2024) Vol. 12, Iss. 7, pp. 140-140
Open Access | Times Cited: 11
RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis
Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, et al.
Analytical Chemistry (2024) Vol. 96, Iss. 21, pp. 8492-8500
Open Access | Times Cited: 8
Exploring the various aspects of Surface enhanced Raman spectroscopy (SERS) with focus on the recent progress: SERS-active substrate, SERS-instrumentation, SERS-application
Richa Goel, Sibashish Chakraborty, Vimarsh Awasthi, et al.
Sensors and Actuators A Physical (2024) Vol. 376, pp. 115555-115555
Closed Access | Times Cited: 8
Artifacts and Anomalies in Raman Spectroscopy: A Review on Origins and Correction Procedures
Ravi teja Vulchi, Volodymyr Morgunov, Rajendhar Junjuri, et al.
Molecules (2024) Vol. 29, Iss. 19, pp. 4748-4748
Open Access | Times Cited: 8
Non-destructive origin and ginsenoside analysis of American ginseng via NIR and deep learning
Peng Li, Siqi Wang, Lin Yu, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2025) Vol. 334, pp. 125913-125913
Closed Access | Times Cited: 1
Machine learning-assisted Fourier transform infrared spectroscopy to predict adulteration in coriander powder
Rishabh Goyal, Poonam Singha, Sushil Kumar Singh
Food Chemistry (2025) Vol. 477, pp. 143502-143502
Closed Access | Times Cited: 1
Visualization of a Machine Learning Framework toward Highly Sensitive Qualitative Analysis by SERS
Siheng Luo, Weili Wang, Zhifan Zhou, et al.
Analytical Chemistry (2022) Vol. 94, Iss. 28, pp. 10151-10158
Closed Access | Times Cited: 28
Recent advances of Raman spectroscopy for the analysis of bacteria
Linsey Rodriguez, Zhiyun Zhang, Danhui Wang
Analytical Science Advances (2023) Vol. 4, Iss. 3-4, pp. 81-95
Open Access | Times Cited: 22
Commentary on the review articles of spectroscopy technology combined with chemometrics in the last three years
Xuesong Huo, Pu Chen, Jingyan Li, et al.
Applied Spectroscopy Reviews (2023) Vol. 59, Iss. 4, pp. 423-482
Closed Access | Times Cited: 21
Recent advances in nano/microfabricated substrate platforms and artificial intelligence for practical surface-enhanced Raman scattering-based bioanalysis
P. P. Praveen Kumar, Shimayali Kaushal, Dong‐Kwon Lim
TrAC Trends in Analytical Chemistry (2023) Vol. 168, pp. 117341-117341
Closed Access | Times Cited: 21
Raman Spectroscopy and AI Applications in Cancer Grading: An Overview
Pietro Manganelli Conforti, Gianmarco Lazzini, Paolo Russo, et al.
IEEE Access (2024) Vol. 12, pp. 54816-54852
Open Access | Times Cited: 6
Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network
Conor D. Rankine, Thomas J. Penfold
The Journal of Chemical Physics (2022) Vol. 156, Iss. 16
Open Access | Times Cited: 28
Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders
Dimitar Georgiev, A. Fernandez-Galiana, Simon Vilms Pedersen, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 45
Open Access | Times Cited: 5
Does DMSO affect the conformational changes of drug molecules in supercritical CO2 Media?
Ilya A. Khodov, Konstantin V. Belov, М. А. Krest’yaninov, et al.
Journal of Molecular Liquids (2023) Vol. 384, pp. 122230-122230
Closed Access | Times Cited: 11
Characterization and discrimination of spike protein in SARS‐CoV‐2 virus‐like particles via surface‐enhanced Raman spectroscopy
Münevver Akdeniz, Zakarya Al‐Shaebi, Mine Altunbek, et al.
Biotechnology Journal (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 11
Rapid and accurate identification of stem cell differentiation stages via SERS and convolutional neural networks
Xiao Zhang, Jianhui Wan, Tao Huang, et al.
Biomedical Optics Express (2024) Vol. 15, Iss. 5, pp. 2753-2753
Open Access | Times Cited: 4
Local deep learning of principal component regression model for spectroscopic calibration of time-varying spectra data
Junhua Zheng, Hai Zhou, Xinyu Liu, et al.
Measurement (2025), pp. 116855-116855
Closed Access
Development of machine learning enhanced low-cost spectrophotometer for pesticide prediction
S. Murathathunyaluk, Maturada Jinorose, K. Janpetch, et al.
Measurement (2025), pp. 116890-116890
Closed Access
Applied Artificial Intelligence in Materials Science and Material Design
Emigdio Chávez‐Ángel, Martin Eriksen, Alejandro Castro‐Álvarez, et al.
Advanced Intelligent Systems (2025)
Open Access
Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review
Mogos Girmatsion, Xiaoqian Tang, Qi Zhang, et al.
Food Research International (2025), pp. 116285-116285
Closed Access
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