• Home
  • Search
  • Machine learning approaches classify clinical malaria outcomes based on haematological parameters
  • Cite Icon34
  • https://doi.org/10.1186/s12916-020-01823-3Copy DOI Icon

Machine learning approaches classify clinical malaria outcomes based on haematological parameters

Show More
  • Abstract
  • Highlights & Summary
  • PDF
  • Literature Map
  • References
  • Citations
  • Similar Papers
Abstract

BackgroundMalaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI), remains a challenge. Furthermore, the success of rapid diagnostic tests (RDTs) is threatened by Pfhrp2/3 deletions and decreased sensitivity at low parasitaemia. Analysis of haematological indices can be used to support the identification of possible malaria cases for further diagnosis, especially in travellers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM, and severe malaria (SM) using haematological parameters.MethodsWe obtained haematological data from 2,207 participants collected in Ghana: nMI (n = 978), SM (n = 526), and UM (n = 703). Six different ML approaches were tested, to select the best approach. An artificial neural network (ANN) with three hidden layers was used for multi-classification of UM, SM, and uMI. Binary classifiers were developed to further identify the parameters that can distinguish UM or SM from nMI. Local interpretable model-agnostic explanations (LIME) were used to explain the binary classifiers.ResultsThe multi-classification model had greater than 85% training and testing accuracy to distinguish clinical malaria from nMI. To distinguish UM from nMI, our approach identified platelet counts, red blood cell (RBC) counts, lymphocyte counts, and percentages as the top classifiers of UM with 0.801 test accuracy (AUC = 0.866 and F1 score = 0.747). To distinguish SM from nMI, the classifier had a test accuracy of 0.96 (AUC = 0.983 and F1 score = 0.944) with mean platelet volume and mean cell volume being the unique classifiers of SM. Random forest was used to confirm the classifications, and it showed that platelet and RBC counts were the major classifiers of UM, regardless of possible confounders such as patient age and sampling location.ConclusionThe study provides proof of concept methods that classify UM and SM from nMI, showing that the ML approach is a feasible tool for clinical decision support. In the future, ML approaches could be incorporated into clinical decision-support algorithms for the diagnosis of acute febrile illness and monitoring response to acute SM treatment particularly in endemic settings.

Loading PDF

Similar Papers
  • Research Article
  • Citations89

Lung injury in uncomplicated and severe falciparum malaria: a longitudinal study in papua, Indonesia.

  • Nov 01, 2005
  • The Journal of infectious diseases
  • Graeme P Maguire +6
  • Research Article
  • Citations69

Hematological parameters in tench Tinca tinca after short term exposure to lead

  • Jan 03, 2006
  • Journal of Applied Toxicology
  • Syed Lal Shah
  • Research Article
  • Citations16

Prescription patterns and compliance with World Health Organization recommendations for the management of uncomplicated and severe malaria: A prospective, real-world study in sub-Saharan Africa

  • Jul 25, 2023
  • Malaria Journal
  • Vito Baraka +17
  • Discussion
  • Citations33

Cerebral Malaria: A Vasculopathy

  • Mar 01, 2010
  • The American journal of pathology
  • Mahalia S Desruisseaux +4
  • Research Article
  • Citations6

Data-driven rapid detection of Helicobacter pylori infection through machine learning with limited laboratory parameters in Chinese primary clinics

  • Aug 01, 2024
  • Heliyon
  • Shiben Zhu +4
  • Research Article

COMPARISON OF RED CELL INDICES IN IRON DEFICIENCY ANEMIA AND BETA THALASSEMIA MINOR IN CHILDREN AGE 6 MONTHS TO 2 YEARS

  • Jul 17, 2025
  • Pakistan Journal of Intensive Care Medicine
  • G Khan +5
  • Research Article

The value of complete blood count parameters in the preoperative diagnosis of parathyroid tumor

  • Sep 26, 2025
  • Gland Surgery
  • Qingyuan Zheng +6
  • Research Article

The Role of Oral Chloroquine Treatment in the Home-Based Management of Childhood Malaria in Jos, Nigeria: Biochemical, Hematological, Nutritional, and Co-Infection Perspectives

  • Jan 01, 2024
  • Advances in Infectious Diseases
  • Segun Afolabi Olomu +3
  • PDF
  • Research Article
  • Citations25

Hematological indices and abnormalities among patients with uncomplicated falciparum malaria in Kosti city of the White Nile state, Sudan: a comparative study

  • May 31, 2021
  • BMC Infectious Diseases
  • Ahmed M E Elkhalifa +9
  • PDF
  • Research Article
  • Citations45

Increased interleukin-6 levels associated with malaria infection and disease severity: a systematic review and meta-analysis

  • Apr 08, 2022
  • Scientific Reports
  • Polrat Wilairatana +5
  • Research Article
  • Citations13

Blood indices to differentiate between β-thalassemia trait and iron deficiency anemia in adult healthy Egyptian blood donors

  • Jan 01, 2014
  • The Egyptian Journal of Haematology
  • Aelsalakawy Walaa +3
  • Research Article
  • Citations1

Effects of FSH extracted from in vitro cultured anterior pituitary cells of male buffalo calves on body and testes weight, serum FSH and total cholesterol and hematological variables in male rabbits

  • Sep 28, 2014
  • Animal Reproduction Science
  • Muhammad Riaz Naveed +6
  • Research Article
  • Citations1

Reference values for the erythrocytic profile of Anak 2000 broilers and Lohmann brown pullets in Nsukka, Eastern Nigeria

  • Feb 24, 2007
  • Comparative Clinical Pathology
  • J O A Okoye +2
  • Research Article
  • Citations4

Decreased Microvascular Function in Tanzanian Children With Severe and Uncomplicated Falciparum Malaria

  • Apr 01, 2017
  • Open Forum Infectious Diseases
  • Tsin W Yeo +7
  • Research Article
  • Citations34

Patient posture for blood collection by venipuncture: recall for standardization after 28 years

  • Jan 01, 2017
  • Revista Brasileira de Hematologia e Hemoterapia
  • Gabriel Lima-Oliveira +5
Cactus Communications logo

Copyright 2026 Cactus Communications. All rights reserved.