A novel deep learning framework for accurate melanoma diagnosis integrating imaging and genomic data for improved patient outcomes.

Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Published Date: Jun 1, 2024

Abstract

BACKGROUND: Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays an important role in improving patients' prognosis. Biopsy is the traditional method for melanoma diagnosis, but this method lacks reliability. Therefore, it is important to apply new methods to diagnose melanoma effectively.

Authors

  • Ajmeera Kiran
    Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India.
  • Navaprakash Narayanasamy
    Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, India.
  • Janjhyam Venkata Naga Ramesh
    Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India.
  • Mohd Wazih Ahmad
    Chair Intelligent Systems SIG, Adama Science and Technology University, ASTU, Adama, Ethiopia.

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