AIMC Topic: Malaria, Falciparum

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Machine learning enables de novo multiepitope design of circumsporozoite protein to target trimeric L9 antibody.

Proceedings of the National Academy of Sciences of the United States of America
Currently approved vaccines for the prevention of malaria provide only partial protection against disease due to high variability in the quality of induced antibodies. These vaccines present the unstructured central repeat region, as well as the C-te...

Determinants of malaria transmission in Indian districts in 2018: insights from ensemble models.

Malaria journal
BACKGROUND: The National Framework for Malaria Elimination, formulated in 2016, aims to eliminate malaria in India by 2030, focusing on the districts as the strategic units for planning and implementing intervention measures. In this study, the spati...

How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms.

Malaria journal
BACKGROUND: Machine learning algorithms have been used to predict malaria risk and severity, identify immunity biomarkers for malaria vaccine candidates, and determine molecular biomarkers of antimalarial drug resistance. Developing these prediction ...

MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d'Ivoire.

Malaria journal
BACKGROUND: In sub-Saharan Africa, Plasmodium falciparum is the most prevalent species of malaria parasites. In endemic areas, malaria is mainly diagnosed using microscopy or rapid diagnostic tests (RDTs), which have limited sensitivity, and microsco...

Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Communications biology
Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasite Plasmodium falciparum faces challenges due to photosensitivity, small parasite size, and the anisotropy and large refractive index of host erythroc...

Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax.

Scientific reports
Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI)...

Generalized fractional optimization-based explainable lightweight CNN model for malaria disease classification.

Computers in biology and medicine
Over the past few decades, machine learning and deep learning (DL) have incredibly influenced a broader range of scientific disciplines. DL-based strategies have displayed superior performance in image processing compared to conventional standard met...

Diagnosis of infections using artificial intelligence techniques versus standard microscopy in a reference laboratory.

Journal of clinical microbiology
Diagnosing malaria using standard techniques is time-consuming. With limited staffing in many laboratories, this may lead to delays in reporting. Innovative technologies are changing the diagnostic landscape and may help alleviate staffing shortages....

Machine learning prediction of malaria vaccine efficacy based on antibody profiles.

PLoS computational biology
Immunization through repeated direct venous inoculation of Plasmodium falciparum (Pf) sporozoites (PfSPZ) under chloroquine chemoprophylaxis, using the PfSPZ Chemoprophylaxis Vaccine (PfSPZ-CVac), induces high-level protection against controlled huma...

Reagent-free detection of Plasmodium falciparum malaria infections in field-collected mosquitoes using mid-infrared spectroscopy and machine learning.

Scientific reports
Field-derived metrics are critical for effective control of malaria, particularly in sub-Saharan Africa where the disease kills over half a million people yearly. One key metric is entomological inoculation rate, a direct measure of transmission inte...