Recent progresses in machine learning assisted Raman spectroscopy

Y Qi, D Hu, Y Jiang, Z Wu, M Zheng… - Advanced Optical …, 2023 - Wiley Online Library
With the development of Raman spectroscopy and the expansion of its application domains,
conventional methods for spectral data analysis have manifested many limitations. Exploring …

Raman spectroscopy and its modifications applied to biological and medical research

ES Allakhverdiev, VV Khabatova, BD Kossalbayev… - Cells, 2022 - mdpi.com
Nowadays, there is an interest in biomedical and nanobiotechnological studies, such as
studies on carotenoids as antioxidants and studies on molecular markers for cardiovascular …

Current trends of Raman spectroscopy in clinic settings: opportunities and challenges

Y Wang, L Fang, Y Wang, Z **ong - Advanced Science, 2024 - Wiley Online Library
Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can
lead to timely and effective medical treatment. The current conventional clinical methods …

Advancing Raman spectroscopy from research to clinic: Translational potential and challenges

S Tanwar, SK Paidi, R Prasad, R Pandey… - Spectrochimica Acta Part …, 2021 - Elsevier
Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique
due to its ability to provide molecule-specific information with ultrahigh sensitivity at near …

[HTML][HTML] A systematic review on early prediction of Mild cognitive impairment to alzheimers using machine learning algorithms

KPM Niyas, P Thiyagarajan - International Journal of Intelligent Networks, 2023 - Elsevier
Background A person consults a doctor when he or she is suspicious of their cognitive
abilities. Finding patients who can be converted into Alzheimer's in the future is a difficult …

An extreme learning machine optimized by differential evolution and artificial bee colony for predicting the concentration of whole blood with Fourier Transform Raman …

Q Wang, S Song, L Li, D Wen, P Shan, Z Li… - Spectrochimica Acta Part …, 2023 - Elsevier
Raman spectroscopy, with its advantages of non-contact nature, rapid detection, and
minimum water interference, is promising for non-invasive blood detection or diagnosis in …

[HTML][HTML] Raman spectroscopy techniques for the investigation and diagnosis of Alzheimer's disease

P Polykretis, M Banchelli, C D'Andrea… - Frontiers in Bioscience …, 2022 - imrpress.com
Alzheimer's disease (AD) is the most common neurodegenerative disorder, resulting in
memory loss, cognitive decline, bodily function impairment, and finally death. The growing …

Machine learning for prediction, classification, and identification of immobilized enzymes for biocatalysis

NM Ralbovsky, JP Smith - Pharmaceutical Research, 2023 - Springer
Background Enzyme immobilization is a beneficial component involved in biocatalytic
strategies. Understanding and evaluating the enzyme immobilization system plays an …

Vibrational spectroscopy for detection of diabetes: A review

NM Ralbovsky, IK Lednev - Applied spectroscopy, 2021 - opg.optica.org
Type II diabetes mellitus (T2DM) is a metabolic disorder that is characterized by chronically
elevated glucose caused by insulin resistance. Although T2DM is manageable through …

[HTML][HTML] Harnessing topological machine learning in Raman spectroscopy: Perspectives for Alzheimer's disease detection via cerebrospinal fluid analysis

F Conti, M Banchelli, V Bessi, C Cecchi, F Chiti… - Journal of the Franklin …, 2024 - Elsevier
The cerebrospinal fluid of 21 subjects who received a clinical diagnosis of Alzheimer's
disease (AD) as well as of 22 pathological controls has been collected and analysed by …