Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering
Abstract Machine learning is shaping up our lives in many ways. In analytical sciences,
machine learning provides an unprecedented opportunity to extract information from …
machine learning provides an unprecedented opportunity to extract information from …
The emerging role of Raman spectroscopy as an omics approach for metabolic profiling and biomarker detection toward precision medicine
Omics technologies have rapidly evolved with the unprecedented potential to shape
precision medicine. Novel omics approaches are imperative toallow rapid and accurate data …
precision medicine. Novel omics approaches are imperative toallow rapid and accurate data …
Collagen: quantification, biomechanics and role of minor subtypes in cartilage
BJ Bielajew, JC Hu, KA Athanasiou - Nature Reviews Materials, 2020 - nature.com
Collagen is a ubiquitous biomaterial in vertebrate animals. Although each of its 28 subtypes
contributes to the functions of many different tissues in the body, most studies on collagen or …
contributes to the functions of many different tissues in the body, most studies on collagen or …
Recent trends in SERS-based plasmonic sensors for disease diagnostics, biomolecules detection, and machine learning techniques
Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool
for applications in biology and medicine owing to its ease-of-use, non-destructive, and label …
for applications in biology and medicine owing to its ease-of-use, non-destructive, and label …
Recent advances of Au@ Ag core–shell SERS‐based biosensors
G Awiaz, J Lin, A Wu - Exploration, 2023 - Wiley Online Library
The methodological advancements in surface‐enhanced Raman scattering (SERS)
technique with nanoscale materials based on noble metals, Au, Ag, and their bimetallic alloy …
technique with nanoscale materials based on noble metals, Au, Ag, and their bimetallic alloy …
Potential value and impact of data mining and machine learning in clinical diagnostics
M Saberi-Karimian, Z Khorasanchi… - Critical reviews in …, 2021 - Taylor & Francis
Data mining involves the use of mathematical sciences, statistics, artificial intelligence, and
machine learning to determine the relationships between variables from a large sample of …
machine learning to determine the relationships between variables from a large sample of …
Recent advances of utilizing artificial intelligence in lab on a chip for diagnosis and treatment
Nowadays, artificial intelligence (AI) creates numerous promising opportunities in the life
sciences. AI methods can be significantly advantageous for analyzing the massive datasets …
sciences. AI methods can be significantly advantageous for analyzing the massive datasets …
Machine learning enhances the performance of bioreceptor-free biosensors
KE Schackart III, JY Yoon - Sensors, 2021 - mdpi.com
Since their inception, biosensors have frequently employed simple regression models to
calculate analyte composition based on the biosensor's signal magnitude. Traditionally …
calculate analyte composition based on the biosensor's signal magnitude. Traditionally …
[HTML][HTML] Recent progress of biomarker detection sensors
R Liu, X Ye, T Cui - Research, 2020 - spj.science.org
Early cancer diagnosis and treatment are crucial research fields of human health. One
method that has proven efficient is biomarker detection which can provide real-time and …
method that has proven efficient is biomarker detection which can provide real-time and …
Exploiting machine learning for bestowing intelligence to microfluidics
Intelligent microfluidics is an emerging cross-discipline research area formed by combining
microfluidics with machine learning. It uses the advantages of microfluidics, such as high …
microfluidics with machine learning. It uses the advantages of microfluidics, such as high …