{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T21:38:49Z","timestamp":1768513129272,"version":"3.49.0"},"posted":{"date-parts":[[2024,6,5]]},"group-title":"Microbiology","reference-count":29,"publisher":"openRxiv","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,6,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Rodent malaria models serve as important preclinical antimalarial and vaccine testing tools. Evaluating treatment outcomes in these models often requires manually counting parasite-infected red blood cells (iRBCs), a time-consuming process, which can be inconsistent between individuals and labs. We have developed an easy-to-use machine learning (ML)-based software, Malaria Screener R, to expedite and standardize such studies by automating the counting of\n                  <jats:italic>Plasmodium<\/jats:italic>\n                  iRBCs in rodents. This software can process Giemsa-stained blood smear images captured by any camera-equipped microscope. It features an intuitive graphical user interface that facilitates image processing and visualization of the results. The software has been developed as a desktop application that processes images on standard Windows and Mac OS computers. A previous ML model created by the authors designed to count\n                  <jats:italic>P. falciparum<\/jats:italic>\n                  -infected human RBCs did not perform well counting\n                  <jats:italic>Plasmodium<\/jats:italic>\n                  -infected mouse RBCs. We leveraged that model by loading the pre-trained weights and training the algorithm with newly collected data to target\n                  <jats:italic>P. yoelii<\/jats:italic>\n                  and\n                  <jats:italic>P. berghei<\/jats:italic>\n                  mouse iRBCs. This new model reliably measured both\n                  <jats:italic>P. yoelii<\/jats:italic>\n                  and\n                  <jats:italic>P. berghei<\/jats:italic>\n                  parasitemia (R\n                  <jats:sup>2<\/jats:sup>\n                  = 0.9916). Additional rounds of training data to incorporate variances due to length of Giemsa staining, microscopes etc, have produced a generalizable model, meeting WHO Competency Level 1 for the sub-category of parasite counting using independent microscopes. Reliable, automated analyses of blood-stage parasitemia will facilitate rapid and consistent evaluation of novel vaccines and antimalarials across labs in an easily accessible\n                  <jats:italic>in vivo<\/jats:italic>\n                  malaria model.\n                <\/jats:p>","DOI":"10.1101\/2024.06.05.597554","type":"posted-content","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T23:35:14Z","timestamp":1717630514000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of machine learning in a rodent malaria model for rapid, accurate, and consistent parasite counts"],"prefix":"10.64898","author":[{"given":"Sean","family":"Yanik","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nattawat","family":"Chaiyawong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Opeoluwa","family":"Adewale-Fasoro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luciana Ribeiro","family":"Dinis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ravi Kumar","family":"Narayanasamy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth C.","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ariel","family":"Lubonja","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bowen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Jaeger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8370-0553","authenticated-orcid":false,"given":"Prakash","family":"Srinivasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2024060921251048000_2024.06.05.597554v1.1","unstructured":"Organization WH. 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