Retrosynthetic analysis via deep learning to improve pilomatricoma diagnoses.

Journal: Computers in biology and medicine
Published Date: Sep 19, 2024

Abstract

BACKGROUND: Pilomatricoma, a benign childhood skin tumor, presents diagnostic challenges due to its manifestation variations and requires surgical excision upon histological confirmation of its characteristic cellular features. Recent artificial intelligence (AI) advancements in pathology promise enhanced diagnostic accuracy and treatment approaches for this neoplasm.

Authors

  • Zheng Wang
    Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan 430060, China.
  • Xinyu Tan
  • Xue Yang
    Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, China.
  • Hui Hu
    Department of Epidemiology, College of Medicine & College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
  • Kaibin Lin
    School of Computer Science, Hunan First Normal University, Changsha, 410205, China.
  • Chong Wang
    Shandong Xinhua Pharmaceutical Co., Ltd., No. 1, Lu Tai Road, High Tech Zone, Zibo 255199, China.
  • Hongyang Fu
    Department of Dermatology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China; Department of Dermatology, Baoan Women's and Children's Hospital, Jinan University, Shenzhen, 518000, Guangdong, China. Electronic address: fuhongyang2024@outlook.com.
  • Jianglin Zhang
    Department of Detmatology, The Second Clinical Medical College, Shenzhen Peoples Hospital, Jinan University. The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518020, Guangdong, China.

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