用于评估斑秃患者脱发程度的临床适用深度学习框架。
Clinically Applicable Deep Learning Framework for Measurement of the Extent of Hair Loss in Patients With Alopecia Areata.
机构信息
Department of Dermatology and Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Department of Dermatology and Institute of Hair and Cosmetic Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
出版信息
JAMA Dermatol. 2020 Sep 1;156(9):1018-1020. doi: 10.1001/jamadermatol.2020.2188.
Abstract
This study aims to develop a deep learning framework to determine the Severity of Alopecia Tool (SALT) score for measurement of hair loss in patients with alopecia areata.
摘要
本研究旨在开发一种深度学习框架，以确定脱发严重程度评估工具（SALT）评分，用于评估斑秃患者的脱发程度。
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本文引用的文献
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All-Cause and Cause-Specific Mortality Risks Associated With Alopecia Areata: A Korean Nationwide Population-Based Study.斑秃相关的全因死亡率和特定病因死亡率风险：一项基于韩国全国人口的研究。
JAMA Dermatol. 2019 Aug 1;155(8):922-928. doi: 10.1001/jamadermatol.2019.0629.
2
Topographic Phenotypes of Alopecia Areata and Development of a Prognostic Prediction Model and Grading System: A Cluster Analysis.斑秃的拓扑表型和预后预测模型及分级系统的开发：聚类分析。
JAMA Dermatol. 2019 May 1;155(5):564-571. doi: 10.1001/jamadermatol.2018.5894.
3
Association of Out-of-Pocket Health Care Costs and Financial Burden for Patients With Alopecia Areata.斑秃患者自付医疗费用与经济负担的关联。
JAMA Dermatol. 2019 Apr 1;155(4):493-494. doi: 10.1001/jamadermatol.2018.5218.
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Hair Regrowth Outcomes of Contact Immunotherapy for Patients With Alopecia Areata: A Systematic Review and Meta-analysis.接触免疫疗法治疗斑秃患者的毛发再生结果：系统评价和荟萃分析。
JAMA Dermatol. 2018 Oct 1;154(10):1145-1151. doi: 10.1001/jamadermatol.2018.2312.
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