AIMC Topic: Malaria

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Discovery of potential 1,3,5-Triazine compounds against strains of Plasmodium falciparum using supervised machine learning models.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences Dec 25, 2019
The Malaria burden was an escalating global encumbrance and need to be addressed with critical care. Anti-malarial drug discovery was integrated with supervised machine learning (ML) models to identify potent thiazolyl-traizine derivatives. This assi...
Antimalarials Triazines Parasitemia Chloroquine Machine Learning Plasmodium falciparum Malaria
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Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears.

IEEE journal of biomedical and health informatics Sep 23, 2019
OBJECTIVE: This work investigates the possibility of automated malaria parasite detection in thick blood smears with smartphones.
Malaria Image Interpretation, Computer-Assisted Hematologic Tests Parasitology Smartphone Predictive Value of Tests Plasmodium falciparum Neural Networks, Computer Deep Learning Humans
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Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks.

PloS one Aug 14, 2019
BACKGROUND: Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a re...
Aging Spectroscopy, Near-Infrared Models, Statistical Malaria Female Animals Male Population Density Plasmodium Anopheles Neural Networks, Computer
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Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.

Malaria journal May 30, 2019
BACKGROUND: The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Hum...
Humans Female Animals Logistic Models Vertebrates Anopheles Host Specificity Blood Supervised Machine Learning Feeding Behavior Mosquito Vectors Spectrophotometry, Infrared Chickens Malaria Goats
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Artificial Intelligence for infectious disease Big Data Analytics.

Infection, disease & health Nov 2, 2018
BACKGROUND: Since the beginning of the 21st century, the amount of data obtained from public health surveillance has increased dramatically due to the advancement of information and communications technology and the data collection systems now in pla...
Humans Artificial Intelligence Communicable Diseases Big Data Disease Eradication Malaria Communicable Disease Control
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Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach.

Scientific reports Aug 27, 2018
The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 400,000 deaths are reported every year, mainly in African children. The diversity of clinical presentations associated w...
Malaria Anemia Malaria, Falciparum Child, Preschool Humans Child Neural Networks, Computer Plasmodium falciparum Phenotype Male Severity of Illness Index Biomarkers Female
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Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells.

Journal of biophotonics May 11, 2018
Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality...
Light Erythrocytes Scattering, Radiation Humans Holography Machine Learning Malaria
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The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.

Journal of biomedical informatics Feb 27, 2018
INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important pre...
Climate Wavelet Analysis Communicable Disease Control Hand, Foot and Mouth Disease Chickenpox Dengue Infectious Disease Medicine Taiwan Singapore Malaria Japan Thailand Humans Incidence Communicable Diseases Models, Statistical Machine Learning Reproducibility of Results Public Health Algorithms Disease Outbreaks Forecasting
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Image analysis and machine learning for detecting malaria.

Translational research : the journal of laboratory and clinical medicine Jan 12, 2018
Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts a...
Humans Machine Learning Blood Sedimentation Smartphone Staining and Labeling Malaria
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Spatiotemporal Bayesian networks for malaria prediction.

Artificial intelligence in medicine Dec 11, 2017
Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been use...
Animals Time Factors Nonlinear Dynamics Humans ROC Curve Disease Vectors Neural Networks, Computer Thailand Bayes Theorem Area Under Curve Artificial Intelligence Incidence Malaria
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