RECOMED: A comprehensive pharmaceutical recommendation system.

Journal: Artificial intelligence in medicine
PMID: 39306906

Abstract

OBJECTIVES: To build datasets containing useful information from drug databases and recommend a list of drugs to physicians and patients with high accuracy by considering a wide range of features of people, diseases, and chemicals.

Authors

  • Mariam Zomorodi
    Department of Computer Science, Faculty of Computer Science and Telecommunications, Cracow University of Technology, Krakow, Poland. Electronic address: zomorodi@pk.edu.pl.
  • Ismail Ghodsollahee
    Department of Computer Engineering, Ferdowsi University of Mashhad, Iran.
  • Jennifer H Martin
    NHMRC Centre for Research Excellence in Digestive Health, Hunter Medical Research Institute (HMRI), The University of Newcastle, Callaghan, New South Wales, Australia.
  • Nicholas J Talley
    High-Value Nutrition National Science Challenge, Auckland, New Zealand.
  • Vahid Salari
    Institute for Quantum Science and Technology, Department of Physics and Astronomy, University of Calgary, Alberta, Canada.
  • Pawel Plawiak
    Institute of Telecomputing, Faculty of Physics, Mathematics and Computer Science, Cracow University of Technology, Krakow, Poland.
  • Kazem Rahimi
    Deep Medicine, Oxford Martin School, Oxford, United Kingdom.
  • U R Acharya
    School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD, Australia.

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