Revolutionizing Alopecia Care: Integrating Machine Learning for Diagnosis and Treatment Optimization

Ranjeet Kumar

Revolutionizing Alopecia Care: Integrating Machine Learning for Diagnosis and Treatment Optimization

Authors: Ranjeet Kumar

Unique Paper ID: 179037
Volume: 11
Issue: 12
PageNo: 5277-5283

Keywords: Androgenetic Alopecia Minoxidil Baldness Alopecia Areata JAK inhibitors hair transplantation SALT Scoring Trichoscopic Analysis Personalized Medicine.

Abstract:
Androgenetic alopecia is a diagnosis of hair loss that impacts both genders marked by hair thinning and specific balding patterns. It is mainly influenced by hormonal factors with dihydrotestosterone playing a role, in inhibiting the growth of hair. The condition involves an interaction of elements within the hair follicles leading to shorter and finer hairs over time. This condition can have effects on individuals it affects, impacting their quality of life and self-perception. Understanding the prevalence of alopecia in both genders is vital as rates vary among racial groups. The development and progression of this condition involve the shrinking of hair follicles due to hormone activity, particularly dihydrotestosterone. Several medical treatment options exist for women with alopecia including minoxidil and finasteride each having its effectiveness and potential side effects. Recent advancements in artificial intelligence (AI) and machine learning (ML) have revolutionized alopecia care by enabling more precise diagnosis, personalized treatment plans, and real-time monitoring of disease progression. AI-driven tools such as automated trichoscopic analysis, robotic hair transplant systems, and AI-powered Severity of Alopecia Tool (SALT) scoring automation have significantly enhanced diagnostic accuracy and therapeutic outcomes. This paper explores the integration of AI in alopecia care, highlighting its role in improving diagnostic precision, optimizing treatment strategies, and fostering advancements in personalized medicine.

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ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 5277-5283

Revolutionizing Alopecia Care: Integrating Machine Learning for Diagnosis and Treatment Optimization

Available:https://ijirt.org/Article?manuscript=179037

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UGC Approved
Journal no 47859

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