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Related Concept Videos

Skin Cancer01:30

Skin Cancer

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Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
Basal Cell Carcinoma (BCC): BCC is the most common type of skin cancer, accounting for about 80% of cases. It typically develops in...
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Updated: May 24, 2025

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ
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Identifying Features for Keloid Scars Subtyping Using K-Modes Clustering.

Anirudh Jaishankar, Neha Jain, Andrew Hornback

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    |March 5, 2025
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    Summary
    This summary is machine-generated.

    Keloids are abnormal scars resulting from excessive collagen. This study used k-modes clustering on ICD-10 codes to identify risk factors like skin fibrosis and specific burn locations, aiding in targeted prevention.

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    Area of Science:

    • Dermatology
    • Medical Informatics
    • Computational Biology

    Background:

    • Keloids are pathological scars from abnormal wound healing, marked by excessive collagen.
    • They exceed original lesion sites, leading to cosmetic issues, discomfort, and reduced quality of life.
    • Current treatments offer limited long-term relief due to poor understanding of keloid causes.

    Purpose of the Study:

    • To identify predictive risk factors for keloid scar formation.
    • To analyze patterns in medical history data for patients with hypertrophic skin disorders.
    • To leverage a data-driven approach for understanding keloid etiology.

    Main Methods:

    • Utilized the k-modes clustering algorithm.
    • Analyzed International Classification of Diseases, 10th Revision (ICD-10) medical codes.
    • Examined patient medical histories within a cohort of individuals with hypertrophic skin disorders.

    Main Results:

    • Identified scar conditions and fibrosis of the skin (L905) as significant features.
    • Found specific burn locations (shoulder/upper limb T22, trunk T21, ankle/foot T25) strongly associated with keloid occurrence.
    • Highlighted clusters with high keloid frequency based on these ICD-10 codes.

    Conclusions:

    • Clustering analysis effectively identifies key factors associated with keloid scars.
    • Findings can inform targeted prevention and management strategies for susceptible individuals.
    • This approach may help reduce the incidence and burden of keloids.