Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning.
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| Title: | Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning. |
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| Authors: | Sikulu-Lord MT; School of the Environment, Faculty of Science, The University of Queensland, Brisbane, Queensland, Australia., Edstein MD; Department of Drug Evaluation, Australian Defence Force Malaria and Infectious Disease Institute, Brisbane, Queensland, Australia., Goh B; School of the Environment, Faculty of Science, The University of Queensland, Brisbane, Queensland, Australia., Lord AR; Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia., Travis JA; Department of Drug Evaluation, Australian Defence Force Malaria and Infectious Disease Institute, Brisbane, Queensland, Australia., Dowell FE; Center for Grain and Animal Health Research, USDA Agricultural Research Service, Manhattan, Kansas, United States of America., Birrell GW; Department of Drug Evaluation, Australian Defence Force Malaria and Infectious Disease Institute, Brisbane, Queensland, Australia., Chavchich M; Department of Drug Evaluation, Australian Defence Force Malaria and Infectious Disease Institute, Brisbane, Queensland, Australia. |
| Source: | PloS one [PLoS One] 2024 Mar 25; Vol. 19 (3), pp. e0289232. Date of Electronic Publication: 2024 Mar 25 (Print Publication: 2024). |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0289232 |
