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However, variability in experimental CM (ECM) incidence, onset, and mortality introduce challenges when analyses rely solely on infection day, which may reflect different disease stages among animals. Methods: We applied machine learning to predict ECM risk and onset in a cohort of 153 C57BL\/6, 164 CBA, and 53 Swiss Webster mice. First, we fitted a logistic regression model to estimate the risk of ECM at any day using parasitemia data from day 1 to day 4. Next, we developed and trained a Random Forest Regressor model to predict the exact day of symptom onset. Results: A total of 64.5% of the cohort developed ECM, with onset ranging between 5 and 11 days. Early increases in parasitemia were strong predictors for the development of ECM, with an increase in parasitemia equal to or greater than 0.05 between day 1 and day 3 predicting the development of ECM with 97% sensitivity. The Random Forest model predicted the day of ECM onset with high precision (mean absolute error: 0.43, R2: 0.64). Conclusion: Parasitemia dynamics can effectively identify mice at high risk of ECM, enabling more accurate modeling of early pathological processes and improving the consistency of experimental analyses.<\/jats:p>","DOI":"10.3390\/pathogens14070676","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T13:44:19Z","timestamp":1752241459000},"page":"676","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Temporal Parasitemia Trends Predict Risk and Timing of Experimental Cerebral Malaria in Mice Infected by Plasmodium berghei ANKA"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0727-9565","authenticated-orcid":false,"given":"Peyton J.","family":"Murin","sequence":"first","affiliation":[{"name":"Department of Neurology, Saint Louis University School of Medicine, St. Louis, MO 63104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9075-1470","authenticated-orcid":false,"given":"Cl\u00e1udio Tadeu","family":"Daniel-Ribeiro","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio de Pesquisa em Mal\u00e1ria, Instituto Oswaldo Cruz and Centro de Pesquisa, Diagn\u00f3stico e Treinamento em Mal\u00e1ria, Funda\u00e7\u00e3o Oswaldo Cruz, Rio de Janeiro 21040-360, RJ, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0133-6430","authenticated-orcid":false,"given":"Leonardo Jos\u00e9 Moura","family":"Carvalho","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio de Pesquisa em Mal\u00e1ria, Instituto Oswaldo Cruz and Centro de Pesquisa, Diagn\u00f3stico e Treinamento em Mal\u00e1ria, Funda\u00e7\u00e3o Oswaldo Cruz, Rio de Janeiro 21040-360, RJ, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4220-4979","authenticated-orcid":false,"given":"Yuri Chaves","family":"Martins","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Saint Louis University School of Medicine, St. Louis, MO 63110, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"ref_1","unstructured":"WHO (2024). 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