[HTML][HTML] Emergence of Raman spectroscopy as a probing tool for theranostics
Although medical advances have increased our grasp of the amazing morphological,
genetic, and phenotypic diversity of diseases, there are still significant technological barriers …
genetic, and phenotypic diversity of diseases, there are still significant technological barriers …
Deep learning data augmentation for Raman spectroscopy cancer tissue classification
Abstract Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive
way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular …
way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular …
On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks
In this paper, we present an analysis of the performance of Raman spectroscopy, combined
with feed-forward neural networks (FFNN), for the estimation of concentration percentages of …
with feed-forward neural networks (FFNN), for the estimation of concentration percentages of …
Quantification of glycated hemoglobin and glucose in vivo using Raman spectroscopy and artificial neural networks
N González-Viveros, J Castro-Ramos… - Lasers in Medical …, 2022 - Springer
Undiagnosed type 2 diabetes (T2D) remains a major public health concern. The global
estimation of undiagnosed diabetes is about 46%, being this situation more critical in …
estimation of undiagnosed diabetes is about 46%, being this situation more critical in …
Skin cancer diagnosis using NIR spectroscopy data of skin lesions in vivo using machine learning algorithms
MB Rocha, FP Loss, PH da Cunha, MP Zanoni… - Biocybernetics and …, 2024 - Elsevier
Skin lesions are classified in benign or malignant. Among the malignant, melanoma is a very
aggressive cancer and the major cause of deaths. So, early diagnosis of skin cancer is very …
aggressive cancer and the major cause of deaths. So, early diagnosis of skin cancer is very …
Transfer Contrastive Learning for Raman Spectroscopy Skin Cancer Tissue Classification
Using Raman spectroscopy (RS) signals for skin cancer tissue classification has recently
drawn significant attention, because of its non-invasive optical technique, which uses …
drawn significant attention, because of its non-invasive optical technique, which uses …
Skin cancer diagnosis using NIR spectroscopy data of skin lesions in vivo using machine learning algorithms
FP Loss, PH da Cunha, MB Rocha, MP Zanoni… - arXiv preprint arXiv …, 2024 - arxiv.org
Skin lesions are classified in benign or malignant. Among the malignant, melanoma is a very
aggressive cancer and the major cause of deaths. So, early diagnosis of skin cancer is very …
aggressive cancer and the major cause of deaths. So, early diagnosis of skin cancer is very …
Machine Learning Approach for Early Detection of Diabetes Using Raman Spectroscopy
The application of machine learning technology for invasive diabetes diagnosis has become
a research trend in medical sectors in recent years. In this research, we utilize the Raman …
a research trend in medical sectors in recent years. In this research, we utilize the Raman …
Peak‐aware adaptive denoising for Raman spectroscopy based on machine learning approach
J Lee, W Lee - Journal of Raman Spectroscopy, 2024 - Wiley Online Library
Raman spectroscopy can be effectively used for detection and analysis of chemical agents
that are serious threats in modern warfare, but the detection and analysis performance is …
that are serious threats in modern warfare, but the detection and analysis performance is …
[图书][B] A novel phase and spectroscopic imaging technique to evaluate cellular functions
TC Khoo - 2022 - search.proquest.com
This thesis presents the application of Raman spectroscopy, digital holographic microscope
(DHM) and transport intensity equation (TIE) in imaging biological samples. Raman …
(DHM) and transport intensity equation (TIE) in imaging biological samples. Raman …