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Recent progresses in machine learning assisted Raman spectroscopy
With the development of Raman spectroscopy and the expansion of its application domains,
conventional methods for spectral data analysis have manifested many limitations. Exploring …
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 …
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 …
lead to timely and effective medical treatment. The current conventional clinical methods …
Advancing Raman spectroscopy from research to clinic: Translational potential and challenges
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 …
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
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 …
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 …
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
Alzheimer's disease (AD) is the most common neurodegenerative disorder, resulting in
memory loss, cognitive decline, bodily function impairment, and finally death. The growing …
memory loss, cognitive decline, bodily function impairment, and finally death. The growing …
Machine learning for prediction, classification, and identification of immobilized enzymes for biocatalysis
Background Enzyme immobilization is a beneficial component involved in biocatalytic
strategies. Understanding and evaluating the enzyme immobilization system plays an …
strategies. Understanding and evaluating the enzyme immobilization system plays an …
Vibrational spectroscopy for detection of diabetes: A review
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 …
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
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 …
disease (AD) as well as of 22 pathological controls has been collected and analysed by …