A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario.

Journal: Computers in biology and medicine
PMID: 39869986

Abstract

BACKGROUND: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite and is responsible for more than 600,000 deaths globally. Early and accurate detection of malaria parasites is crucial for effective treatment, yet conventional microscopy faces limitations in variability and efficiency.

Authors

  • Luca Zedda
    Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124, Cagliari, Italy. Electronic address: luca.zedda@unica.it.
  • Andrea Loddo
    Department of Mathematics and Computer Science, University of Cagliari, via Ospedale 72, 09124, Cagliari, Italy. Electronic address: andrea.loddo@unica.it.
  • Cecilia Di Ruberto
    Department of Mathematics and Computer Science, University of Cagliari, via Ospedale 72, 09124, Cagliari, Italy.

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