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Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning.

Maggy T Sikulu-LordMichael D EdsteinBrendon GohAnton R LordJye A TravisFloyd E DowellGeoffrey W BirrellMarina Chavchich
Published in: PloS one (2024)
These data highlights the potential of NIRS technique as rapid, non-invasive and affordable tool for surveillance of malaria cases. Further work to determine the potential of NIRS to detect malaria in symptomatic and asymptomatic malaria cases in the field is recommended including its capacity to guide current malaria elimination strategies.
Keyphrases
  • plasmodium falciparum
  • machine learning
  • loop mediated isothermal amplification
  • public health
  • big data
  • artificial intelligence
  • electronic health record
  • label free