An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning-Reference-Cited by-同舟云学术

An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning

Published:2021 Issue: Volume: Page:775-783
ISSN:2367-3370
Container-title:Proceedings of 6th International Conference on Recent Trends in Computing
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Author:

Rai Gaurav,Naveen ,Sharma Shubham,Ansari Akbar,Khanduja Namit

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-33-4501-0_71

Reference15 articles.

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2. Gordon K, Tosti A (2011) Alopecia: evaluation and treatment. Clinical Cosmetic Investigational Dermatol 4:101–106. https://doi.org/10.2147/CCID.S10182

3. Darwin E et al (2018) Alopecia Areata: review of epidemiology, clinical features, pathogenesis, and new treatment options. Int J Trichol 10(2):51–60. https://doi.org/10.4103/ijt.ijt_99_17

4. Lloyd GR, Ahmad S, Wasim M, Brereton RG. Pattern recognition of inductively coupled plasma atomic emission spectroscopy of human scalp hair for discriminating between healthy and Hepatitis C patients. Analytica Chimica Acta

5. Linch C, Whiting D, Holland M (2001) Human hair histogenesis for the mitochondrial DNA forensic scientist. J Forensic Sci 46(4):844–853. https://doi.org/10.1520/JFS15056J.ISSN0022-1198

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