PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation.

Journal: Genome medicine
Published Date: Jun 6, 2025

Abstract

BACKGROUND: Current phenotype-based diagnostic tools often struggle with accurate disease prioritization due to incomplete phenotypic data and the complexity of rare disease presentations. Additionally, they lack the ability to generate patient-centered clinical insights or recommend further symptoms for differential diagnosis.

Authors

  • Baole Wen
    College of Medicine, Nankai University, Tianjin, 300350, China.
  • Sheng Shi
    State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China.
  • Yi Long
    State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin 150001, China. scdxhgd@gmail.com.
  • Yanan Dang
    State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China.
  • Weidong Tian
    State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai 200433, PR China; Children's Hospital of Fudan University, Shanghai 200433, PR China. Electronic address: weidong.tian@fudan.edu.cn.

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