Computer-Aided Assessment of Drug-Induced Lung Disease Plausibility

  • Authors:

  • Brigitte Sé/roussi;Jacques Bouaud;Hugette Lioté/;Charles Mayaud

  • Affiliations:

  • Université/ Paris 6, UFR de Mé/decine, Paris, France/ AP-HP, Hô/pital Tenon, Dé/partement de Santé/ Publique, Paris, France;AP-HP, DSI, STIM, Paris, France/ INSERM, UMR_S 872, eq. 20, Paris, France;Université/ Paris 6, UFR de Mé/decine, Paris, France/ AP-HP, Hô/pital Tenon, Dé/partement de Santé/ Publique, Paris, France and Université/ Paris 6, UFR de Mé/decine, P ...;Université/ Paris 6, UFR de Mé/decine, Paris, France/ AP-HP, Hô/pital Tenon, Service de Pneumologie, Paris, France

  • Venue:
  • AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
  • Year:
  • 2007

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Abstract

Drug-induced lung disease (DILD), often suspected in pneumology, is still a diagnostic challenge because of the ever increasing number of pneumotoxic drugs and the large diversity of observed clinical patterns. As a result, DILD can only be evoked as a plausible diagnosis after the exclusion of all other possible causes. PneumoDoc is a computer-based decision support that formalises the evaluation process of the drug-imputability of a lung disease. The knowledge base has been structured as a two-level decision tree. Patient-specific chronological and semiological criteria are first examined leading to the assessment of a qualitative intrinsic DILD plausibility score. Then literature-based data including the frequency of DILD with a given drug and the frequency of the observed clinical situation among the clinical patterns reported with the same drug are evaluated to compute a qualitative extrinsic DILD plausibility score. Based on a simple multimodal qualitative model, extrinsic and intrinsic scores are combined to yield an overall DILD plausibility score.