An approach to the spectral smoothing of Raman data applied to the specific case of thin-film carbon

Laumer, Jonathan; O’Leary, Stephen K.

doi:10.1007/s10854-018-9046-8

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…In this study, we used the Savitzky-Golay (S-G) smoothing filter for denoised smoothing of Raman spectra, in which the polynomial fitting order was set to 2. For baseline correction, the multiple scattering correction (MSC) method was used, which could effectively eliminate the scattering effect of the spectral data and enhance the spectral absorption information related to the molecular compositions ( 38 ). Normalization is a method for simplifying calculation, and a variety of methods have been developed to normalize the Raman spectrum ( 24 ).…”

Section: Methodsmentioning

confidence: 99%

Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study

et al. 2022

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With the low-cost, label-free, and nondestructive features, Raman spectroscopy is becoming an attractive technique with great potential to discriminate bacterial infections. In this pilot study, we analyzed surfaced-enhanced Raman spectroscopy (SERS) spectra via supervised machine learning algorithms, through which we confirmed the application potentials of the SERS technique in rapid and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles.

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Section: Methodsmentioning

confidence: 99%

Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study

et al. 2022

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“…In addition to baseline subtraction and normalisation, smoothing is often used to overcome the inherent issue of noise in Raman spectra. Smoothing is used to remove high‐frequency components from the spectra to reduce noise and simplify the identification of important spectral features 79 . The most used smoothing filter is the Savitsky‐Golay filter, where a polynomial regression is applied to the data, that is, a polynomial curve is fitted to small segments or peaks within the Raman spectrum, with the smoothed curve providing an estimate as to the underlying Raman signal 79,80 .…”

Section: Methodsmentioning

confidence: 99%

“…Smoothing is used to remove high-frequency components from the spectra to reduce noise and simplify the identification of important spectral features. 79 The most used smoothing filter is the Savitsky-Golay filter, where a polynomial regression is applied to the data, that is, a polynomial curve is fitted to small segments or peaks within the Raman spectrum, with the smoothed curve providing an estimate as to the underlying Raman signal. 79,80 The use of a Savitsky-Golay filter for spectral smoothing was employed by three of the studies, 12,61,66 with only Addis et al indicating a filter smoothing width of 9 and a polynomial order of 3.…”

Section: Raman Spectral Pre-processingmentioning

confidence: 99%

“…79 The most used smoothing filter is the Savitsky-Golay filter, where a polynomial regression is applied to the data, that is, a polynomial curve is fitted to small segments or peaks within the Raman spectrum, with the smoothed curve providing an estimate as to the underlying Raman signal. 79,80 The use of a Savitsky-Golay filter for spectral smoothing was employed by three of the studies, 12,61,66 with only Addis et al indicating a filter smoothing width of 9 and a polynomial order of 3. 61 Due to the differences in spectral acquisition and Raman setup, each study required the pre-processing techniques used to be applied in a specific order.…”

Section: Raman Spectral Pre-processingmentioning

confidence: 99%

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Review–Vibrational spectroscopy‐aided diagnosis, prognosis and treatment of inflammatory bowel disease

Buchan,

Oppenheimer

2023

Clinical and Translational Dis

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BackgroundInflammatory bowel disease (IBD) represents a group of chronic gastrointestinal disorders characterised by complex and multifaceted pathologies. The pursuit of non‐invasive, accurate and rapid diagnostic methods and therapeutic monitoring tools has led to the emergence of Raman spectroscopy (RS) as a promising analytical technique in the field of IBD. RS offers molecular specificity with the potential to uncover valuable insights of the pathophysiology of IBD, posing it as a rapidly growing field of interest in both research and clinical settings.MainThis comprehensive review aims to provide an overview of the current state of research in the field of IBD‐RS, with an emphasis on its potential diagnostic, prognostic, and therapeutic monitoring capabilities. We explore the molecular characterisation of bodily fluids including blood, urine and saliva and the ability of RS to rapidly determine the underpinning biochemical changes in their composition. The review also highlights recent studies and advances, that have employed RS to differentiate between healthy and diseased states, classify the IBD subtypes, identify candidate biomarkers and to monitor the therapeutic response to treatment in the form of mucosal healing. Additionally, we comment on the challenges and limitations associated with current research as well as with the clinical translation of RS for IBD diagnosis.ConclusionsAs the field of vibrational spectroscopies continues to evolve particularly in the broader IBD context, to aid the diagnosis, prognosis and treatment, this review serves as a valuable resource for clinicians and researchers alike, examining the potential of Raman‐based spectroscopy and the emerging technologies to advance the understanding and triaging of IBD. Ultimately, the integration of RS into everyday clinical practice holds promise for more effective management of IBDs, addressing the major unmet need in the fields of gastroenterology and of clinical medicine as a whole.

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The D- and G-branches associated with the Raman spectrum of thin-film carbon

Schmidt

Laumer

O’Leary

2023

Solid State Communications

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An approach to the spectral smoothing of Raman data applied to the specific case of thin-film carbon

Cited by 4 publications

References 24 publications

Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study

Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study

Review–Vibrational spectroscopy‐aided diagnosis, prognosis and treatment of inflammatory bowel disease

The D- and G-branches associated with the Raman spectrum of thin-film carbon

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