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Analysis of Skin Cancer and Patient Healthcare Using Data Mining Techniques.

N Arivazhagan1, M A Mukunthan2, D Sundaranarayana3

  • 1Department of Computational Intelligence, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur 603203, India.

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Summary

This study introduces an advanced image analysis technique for early skin cancer detection. By analyzing lesion characteristics like asymmetry, border, color, and diameter, the system aids in timely diagnosis and improved patient outcomes.

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Area of Science:

  • Dermatology
  • Medical Imaging
  • Computational Biology

Background:

  • Skin cancer, characterized by uncontrolled skin cell growth, is primarily caused by DNA damage from ultraviolet (UV) radiation.
  • Early detection of skin cancer is crucial for improving patient survival rates, despite equal incidence in males and females.
  • Understanding the molecular biology and genetics of skin cancer is key to prevention and treatment.

Purpose of the Study:

  • To present an improved image analysis technique for the identification and categorization of skin cancer.
  • To enable routine monitoring of skin alterations for early detection of suspicious lesions.
  • To enhance the accuracy and efficiency of skin cancer diagnosis through automated image processing.

Main Methods:

  • Development of a skin cancer detection system utilizing advanced image processing techniques.
  • Inputting skin lesion images for analysis of texture, size, and shape using Lesion Image Analysis Tools.
  • Feature extraction and image segmentation to assess criteria such as asymmetry, border irregularity, pigment variation, and diameter.

Main Results:

  • The developed system successfully classifies skin images as either normal or indicative of skin cancer.
  • The image analysis technique effectively identifies key dermatological criteria for cancer diagnosis.
  • The approach facilitates early identification of potentially cancerous skin changes.

Conclusions:

  • The proposed image analysis method offers a promising tool for the early and accurate detection of skin cancer.
  • Routine monitoring via this technique can significantly aid in the timely diagnosis of skin cancer.
  • Advancements in diagnostic technology, including image processing, contribute to improved survival rates for skin cancer patients.