Support Vector Machine Classification of Nonmelanoma Skin Lesions Based on Fluorescence Lifetime Imaging Microscopy-Reference-Cited by-同舟云学术

Support Vector Machine Classification of Nonmelanoma Skin Lesions Based on Fluorescence Lifetime Imaging Microscopy

Published:2019-07-17 Issue:16 Volume:91 Page:10640-10647
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Chen Bingling¹^ORCID,Lu Yuan²,Pan Wenhui¹,Xiong Jia¹,Yang Zhigang¹^ORCID,Yan Wei¹,Liu Liwei¹,Qu Junle¹^ORCID

Affiliation:

1. Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China

2. Department of Dermatology, The Sixth People’s Hospital of Shenzhen, Guangdong 518052, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Department of Education of Guangdong Province

Shenzhen Basic Research Project

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.9b01866

Reference33 articles.

1. Teledermatology for the Diagnosis and Management of Skin Cancer

2. Abstract 2022: Twist1 regulates UVB-induced epidermal cell proliferation in non-melanoma skin cancer

3. A randomized study comparing digital imaging to traditional glass slide microscopy for breast biopsy and cancer diagnosis

4. Recent advances in photonic dosimeters for medical radiation therapy

5. Differential proteomic analysis of actinic keratosis, Bowen’s disease and cutaneous squamous cell carcinoma by label-free LC–MS/MS

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