Near-infrared thermo-optical response of the localized reflectance of intact diabetic and nondiabetic human skin

2003 ◽  
Vol 8 (3) ◽  
pp. 534 ◽  
Author(s):  
Shu-jen Yeh ◽  
Omar S. Khalil ◽  
Charles F. Hanna ◽  
Stanislaw Kantor
Keyword(s):  
Human Skin ◽  
Near Infrared ◽  
Optical Response

scholarly journals Machine learning enables discovery of DNA-carbon nanotube sensors for serotonin

2021 ◽  
Author(s):  
Payam Kelich ◽  
Sanghwa Jeong ◽  
Nicole Navarro ◽  
Jaquesta Adams ◽  
Xiaoqi Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Carbon Nanotube ◽  
Dna Sequences ◽  
Regression Models ◽  
Near Infrared ◽  
Optical Response ◽  
Support Vector ◽  
Single Walled Carbon Nanotube ◽  
Nir Fluorescence ◽  
Selective Evolution

AbstractDNA-wrapped single walled carbon nanotube (SWNT) conjugates have remarkable optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response datasets for ~100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ~1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict new unique DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality CNN classifiers and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five new DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches introduce an important new tool to predict useful DNA sequences, which can be used for discovery of new DNA-based sensors and nanobiotechnologies.

Near infrared spectrum simulation applied to human skin for diagnosis

2007 ◽  
Author(s):  
Chen-Mu Tsai ◽  
Yi-Chin Fang ◽  
Chih-Yu Wang ◽  
Pin-Chun Chiu ◽  
Guo-Ying Wu ◽  
...  
Keyword(s):  
Infrared Spectrum ◽  
Human Skin ◽  
Near Infrared ◽  
Spectrum Simulation ◽  
Near Infrared Spectrum

Development of a Method for the Determination of Human Skin Moisture Using a Portable Near-Infrared System

2001 ◽  
Vol 73 (20) ◽  
pp. 4964-4971 ◽  
Author(s):  
Young-Ah Woo ◽  
Jhii-Weon Ahn ◽  
In-Koo Chun ◽  
Hyo-Jin Kim
Keyword(s):  
Human Skin ◽  
Near Infrared ◽  
Skin Moisture

Third-order nonlinear optical response of CuInS2quantum dots—Bright probes for near-infrared biodetection

2013 ◽  
Vol 102 (24) ◽  
pp. 243702 ◽  
Author(s):  
B. Cichy ◽  
D. Wawrzynczyk ◽  
A. Bednarkiewicz ◽  
M. Samoc ◽  
W. Strek
Keyword(s):  
Nonlinear Optical ◽  
Near Infrared ◽  
Optical Response ◽  
Nonlinear Optical Response ◽  
Third Order

Near-infrared autofluorescence imaging of cutaneous melanins and human skin in vivo

2009 ◽  
Vol 14 (2) ◽  
pp. 024017 ◽  
Author(s):  
Xiao Han ◽  
Harvey Lui ◽  
David I. McLean ◽  
Haishan Zeng
Keyword(s):  
Human Skin ◽  
Near Infrared ◽  
Autofluorescence Imaging

Ten new predicted covalent organic frameworks with strong optical response in the visible and near infrared

2015 ◽  
Vol 142 (24) ◽  
pp. 244706 ◽  
Author(s):  
Li-Ming Yang ◽  
Matthew Dornfeld ◽  
Pik-Mai Hui ◽  
Thomas Frauenheim ◽  
Eric Ganz
Keyword(s):  
Near Infrared ◽  
Optical Response ◽  
Covalent Organic Frameworks

Evaluation of variations of biomolecular constituents in human skin in vivo by near-infrared Raman spectroscopy

2001 ◽  
Author(s):  
Zhiwei Huang ◽  
Haishan Zeng ◽  
Calum E. MacAulay ◽  
Iltefat Hamzavi ◽  
David I. McLean ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Human Skin ◽  
Near Infrared
Sign in / Sign up

Export Citation Format

Share Document