iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge (original) (raw)

Abstract

Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) are chronic diseases characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, cognitive). Patients have to manage alternated periods in hospital with care at home, experiencing a constant uncertainty regarding the timing of the disease acute phases and facing a considerable psychological and economic burden that also involves their caregivers. Clinicians, on the other hand, need tools able to support them in all the phases of the patient treatment, suggest personalized therapeutic decisions, indicate urgently needed interventions.

The goal of iDPP@CLEF is to design and develop an evaluation infrastructure for AI algorithms able to:

    1. better describe disease mechanisms;
    1. stratify patients according to their phenotype assessed all over the disease evolution;
    1. predict disease progression in a probabilistic, time dependent fashion.

iDPP@CLEF run as a pilot lab in CLEF 2022, offering tasks on the prediction of ALS progression and a position paper task on explainability of AI algorithms for prediction; 5 groups submitted a total of 120 runs and 2 groups submitted position papers.

iDPP@CLEF will continue in CLEF 2023, focusing on the prediction of MS progression and exploring whether pollution and environmental data can improve the prediction of ALS progression.

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Author information

Authors and Affiliations

  1. University of Lisbon, Lisbon, Portugal
    Helena Aidos, Mamede Alves de Carvalho & Sara C. Madeira
  2. University of Pavia, Pavia, Italy
    Roberto Bergamaschi & Arianna Dagliati
  3. “Città della Salute e della Scienza”, Turin, Italy
    Paola Cavalla
  4. University of Turin, Turin, Italy
    Adriano Chiò & Piero Fariselli
  5. University of Padua, Padua, Italy
    Barbara Di Camillo & Nicola Ferro
  6. Gregorio Marañon Hospital in Madrid, Madrid, Spain
    Jose Manuel García Dominguez
  7. IRCCS Foundation C. Mondino in Pavia, Pavia, Italy
    Eleonora Tavazzi

Authors

  1. Helena Aidos
  2. Roberto Bergamaschi
  3. Paola Cavalla
  4. Adriano Chiò
  5. Arianna Dagliati
  6. Barbara Di Camillo
  7. Mamede Alves de Carvalho
  8. Nicola Ferro
  9. Piero Fariselli
  10. Jose Manuel García Dominguez
  11. Sara C. Madeira
  12. Eleonora Tavazzi

Corresponding author

Correspondence toNicola Ferro .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands
    Jaap Kamps
  2. Université Grenoble-Alpes, Saint-Martin-d’Hères, France
    Lorraine Goeuriot
  3. Università della Svizzera Italiana, Lugano, Switzerland
    Fabio Crestani
  4. University of Copenhagen, Copenhagen, Denmark
    Maria Maistro
  5. University of Tsukuba, Ibaraki, Japan
    Hideo Joho
  6. Dublin City University, Dublin, Ireland
    Brian Davis
  7. Dublin City University, Dublin, Ireland
    Cathal Gurrin
  8. Universität Regensburg, Regensburg, Germany
    Udo Kruschwitz
  9. Dublin City University, Dublin, Ireland
    Annalina Caputo

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Aidos, H. et al. (2023). iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13982. Springer, Cham. https://doi.org/10.1007/978-3-031-28241-6\_57

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