scholarly journals Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM)

APL Photonics ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 040805 ◽  
Author(s):  
Jingfang K. Zhang ◽  
Yuchen R. He ◽  
Nahil Sobh ◽  
Gabriel Popescu
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Interference Microscopy ◽  
Label Free ◽  
Light Interference

Mo1627 - Deep Learning with Big Clinical Data for Prediction of Advanced Neoplasia in Colorectal Cancer Screening of Asymptomatic Adults

2018 ◽  
Vol 154 (6) ◽  
pp. S-774
Author(s):  
Hyo-Joon Yang ◽  
Chang Woo Cho ◽  
Sang Soo Kim ◽  
Kwang-Sung Ahn ◽  
Soo-Kyung Park ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Clinical Data ◽  
Advanced Neoplasia

scholarly journals Intelligent recognition of colorectal cancer combining application of computer-assisted diagnosis with deep learning approaches

2022 ◽  
Vol 12 (1) ◽  
pp. 738
Author(s):  
Akella S. Narasimha Raju ◽  
Kayalvizhi Jayavel ◽  
Tulasi Rajalakshmi
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Premalignant Lesions ◽  
Computer Assisted ◽  
Screening Methods ◽  
Learning Approaches ◽  
Computer Assisted Diagnosis ◽  
Assisted Diagnosis

<span>The malignancy of the colorectal testing methods has been exposed triumph to decrease the occurrence and death rate; this cancer is the relatively sluggish rising and has an extremely peculiar to develop the premalignant lesions. Now, many patients are not going to colorectal cancer screening, and people who do, are able to diagnose existing tests and screening methods. The most important concept of this motivation for this research idea is to evaluate the recognized data from the immediately available colorectal cancer screening methods. The data provided to laboratory technologists is important in the formulation of appropriate recommendations that will reduce colorectal cancer. With all standard colon cancer tests can be recognized agitatedly, the treatment of colorectal cancer is more efficient. The intelligent computer assisted diagnosis (CAD) is the most powerful technique for recognition of colorectal cancer in recent advances. It is a lot to reduce the level of interference nature has contributed considerably to the advancement of the quality of cancer treatment. To enhance diagnostic accuracy intelligent CAD has a research always active, ongoing with the deep learning and machine learning approaches with the associated convolutional neural network (CNN) scheme.</span>

scholarly journals Label-free tissue scanner for colorectal cancer screening

2017 ◽  
Vol 22 (6) ◽  
pp. 066016 ◽  
Author(s):  
Mikhail E. Kandel ◽  
Shamira Sridharan ◽  
Jon Liang ◽  
Zelun Luo ◽  
Kevin Han ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Label Free

scholarly journals A Label-Free, Quantitative Fecal Hemoglobin Detection Platform for Colorectal Cancer Screening

Biosensors ◽  
2017 ◽  
Vol 7 (4) ◽  
pp. 19 ◽  
Author(s):  
Gita Soraya ◽  
Thanh Nguyen ◽  
Chathurika Abeyrathne ◽  
Duc Huynh ◽  
Jianxiong Chan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Label Free

Impedimetric aptasensor for the label-free and selective detection of Interleukin-6 for colorectal cancer screening

2019 ◽  
Vol 137 ◽  
pp. 123-132 ◽  
Author(s):  
Mihaela Tertis ◽  
Petrica Ionut Leva ◽  
Diana Bogdan ◽  
Maria Suciu ◽  
Florin Graur ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Interleukin 6 ◽  
Selective Detection ◽  
Label Free
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