Neural networks for predicting etiological diagnosis of uveitis.

Journal: Eye (London, England)
PMID: 39706896

Abstract

BACKGROUND/OBJECTIVES: The large number and heterogeneity of causes of uveitis make the etiological diagnosis a complex task. The clinician must consider all the information concerning the ophthalmological and extra-ophthalmological features of the patient. Diagnostic machine learning algorithms have been developed and provide a correct diagnosis in one-half to three-quarters of cases. However, they are not integrated into daily clinical practice. The aim is to determine whether machine learning models can predict the etiological diagnosis of uveitis from clinical information.

Authors

  • Robin Jacquot
    Department of Internal Medicine, Hôpital Universitaire de la Croix-Rousse, Hospices Civils de Lyon, University Claude Bernard-Lyon 1, Lyon, France. robin.jacquot@chu-lyon.fr.
  • Lijuan Ren
    School of Software Engineering, Chengdu University of Information Technology, Chengdu, China.
  • Tao Wang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Insaf Mellahk
    DISP UR4570, Jean Monnet Saint-Etienne University, INSA Lyon, Lyon 2 University, Claude Bernard-Lyon 1 University, Roanne, France.
  • Antoine Duclos
    Research on Healthcare Performance RESHAPE, Université Claude Bernard, Lyon 1, France.
  • Laurent Kodjikian
    Department of Ophthalmology, Hôpital Universitaire de la Croix-Rousse, Hospices civils de Lyon, Université Claude Bernard-Lyon 1, Lyon, France.
  • Yvan Jamilloux
    Department of Internal Medicine, Hôpital Universitaire de la Croix-Rousse, Hospices Civils de Lyon, University Claude Bernard-Lyon 1, Lyon, France.
  • Dinu Stanescu
    Department of Ophthalmology, Hôpital Universitaire de la Pitié-Salpêtrière, APHP, Paris, France.
  • Pascal Sève
    Department of Internal Medicine, Hôpital Universitaire de la Croix-Rousse, Hospices Civils de Lyon, University Claude Bernard-Lyon 1, Lyon, France.

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