AIMC Topic: Alopecia Areata

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Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods.

BMC medical informatics and decision making Jan 14, 2025
BACKGROUND: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA.  METHODS: In this study, di...
Humans Machine Learning Biomarkers Gene Expression Profiling Computational Biology Alopecia Areata
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Applications of Machine Learning on Alopecia Areata: A Systematic Review.

Journal of cutaneous medicine and surgery Mar 6, 2024
Humans Machine Learning Alopecia Areata
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Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach.

Computational and mathematical methods in medicine Aug 14, 2021
Alopecia areata is defined as an autoimmune disorder that results in hair loss. The latest worldwide statistics have exhibited that alopecia areata has a prevalence of 1 in 1000 and has an incidence of 2%. Machine learning techniques have demonstrate...
Humans Machine Learning Algorithms Databases, Factual Computational Biology Support Vector Machine Image Interpretation, Computer-Assisted Optical Imaging Hair Alopecia Areata Hair Color
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Clinically Applicable Deep Learning Framework for Measurement of the Extent of Hair Loss in Patients With Alopecia Areata.

JAMA dermatology Sep 1, 2020
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.
Humans Prognosis Severity of Illness Index Deep Learning Image Processing, Computer-Assisted Hair Photography Scalp Alopecia Areata
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