A fluorescence active gold nanorod–quantum dot core–satellite nanostructure for sub-attomolar tumor marker biosensing

RSC Advances ◽  
2015 ◽  
Vol 5 (118) ◽  
pp. 97898-97902 ◽  
Author(s):  
Xiaoling Wu ◽  
Fengli Gao ◽  
Liguang Xu ◽  
Hua Kuang ◽  
Libing Wang ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Quantum Dot ◽  
Tumor Marker ◽  
Cancer Biomarkers ◽  
Gold Nanorod ◽  
Early Diagnosis Of Cancer ◽  
Diagnosis Of Cancer

The accurate monitoring of trace cancer biomarkers is crucial for the early diagnosis of cancer.

A facile deoxyuridine/biotin-modified molecular beacon for simultaneous detection of proteins and nucleic acids via a label-free and background-eliminated fluorescence assay

The Analyst ◽  
2019 ◽  
Vol 144 (18) ◽  
pp. 5504-5510 ◽  
Author(s):  
Fei Yin ◽  
Liqi Liu ◽  
Xia Sun ◽  
Laiyong Hou ◽  
Yu Lu ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Nucleic Acids ◽  
Molecular Beacon ◽  
Simultaneous Detection ◽  
Cancer Biomarkers ◽  
Label Free ◽  
Early Diagnosis Of Cancer ◽  
Different Types ◽  
Diagnosis Of Cancer ◽  
Modified Molecular Beacon

Simultaneous detection of different types of cancer biomarkers (nucleic acids and proteins) could facilitate early diagnosis of cancer and clinical treatment.

scholarly journals On-Chip Liquid Biopsy: Progress in Isolation of Exosomes for Early Diagnosis of Cancer

2017 ◽  
Vol 112 (3) ◽  
pp. 461a ◽  
Author(s):  
Sung Cheol Kim ◽  
Navneet Dogra ◽  
Benjamin H. Wunsch ◽  
Joshua T. Smith ◽  
Stacey M. Gifford ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Liquid Biopsy ◽  
Early Diagnosis Of Cancer ◽  
Diagnosis Of Cancer ◽  
On Chip

A Survey on Using Nature Inspired Computing for Fatal Disease Diagnosis

2017 ◽  
Vol 8 (2) ◽  
pp. 70-91 ◽  
Author(s):  
Prableen Kaur ◽  
Manik Sharma
Keyword(s):  
Early Diagnosis ◽  
Disease Diagnosis ◽  
Fatal Disease ◽  
Swarm Optimization ◽  
Early Diagnosis Of Cancer ◽  
Nature Inspired Computing ◽  
Human Disorders ◽  
Diagnosis Of Cancer ◽  
Individual Use ◽  
Bee Colonies

Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Artificial Bee Colonies (ABC) are some vital nature inspired computing (NIC) techniques. These approaches have been used in early prophecy of various diseases. This article analyzes the efficacy of various NIC techniques in diagnosing diverse critical human disorders. It is observed that GA, ACO, PSO and ABC have been successfully used in early diagnosis of different diseases. As compared to ACO, PSO and ABC algorithms, GA has been extensively used in diagnosis of ecology, cardiology and endocrinologist. In addition, from the last six years of research, it has been observed that the accuracy accomplished using GA, ACO, PSO and ABC in the early diagnosis of cancer, diabetes and cardio problems lies between 73.5%-99.7%, 70%-99.2%, 80%-98% and 76.4% to 99.98% respectively. Furthermore, ACO, PSO and ABC are found to be best suited in diagnosing lung, prostate and breast cancer respectively. Moreover, the hybrid use of NIC techniques produces better results as compared to their individual use.

EARLY DIAGNOSIS OF CANCER

BMJ ◽  
1953 ◽  
Vol 2 (4827) ◽  
pp. 85-85
Author(s):  
H. O gilvie
Keyword(s):  
Early Diagnosis ◽  
Early Diagnosis Of Cancer ◽  
Diagnosis Of Cancer
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