AIMC Topic: Malaria
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Web-Enabled Distributed Health-Care Framework for Automated Malaria Parasite Classification: an E-Health Approach.
Journal of medical systems
Oct 26, 2017
Web-enabled e-healthcare system or computer assisted disease diagnosis has a potential to improve the quality and service of conventional healthcare delivery approach. The article describes the design and development of a web-based distributed health...
Identification of immune signatures predictive of clinical protection from malaria.
PLoS computational biology
Oct 24, 2017
Antibodies are thought to play an essential role in naturally acquired immunity to malaria. Prospective cohort studies have frequently shown how continuous exposure to the malaria parasite Plasmodium falciparum cause an accumulation of specific respo...
Quantum associative memory with linear and non-linear algorithms for the diagnosis of some tropical diseases.
Neural networks : the official journal of the International Neural Network Society
Sep 21, 2017
This paper presents the QAMDiagnos, a model of Quantum Associative Memory (QAM) that can be a helpful tool for medical staff without experience or laboratory facilities, for the diagnosis of four tropical diseases (malaria, typhoid fever, yellow feve...
Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition.
Journal of chemical information and modeling
Mar 17, 2017
The development of new antimalarial therapies is essential, and lowering the barrier of entry for the screening and discovery of new lead compound classes can spur drug development at organizations that may not have large compound screening libraries...
Malaria Parasitemia and Parasite Density in Antiretroviral-Treated HIV-Infected Adults Following Discontinuation of Cotrimoxazole Prophylaxis.
The Journal of infectious diseases
Oct 25, 2016
BACKGROUND:  Cotrimoxazole (CTX) discontinuation increases malaria incidence in human immunodeficiency virus (HIV)-infected individuals. Rates, quantity, and timing of parasitemia rebound following CTX remain undefined.
A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.
BMC systems biology
Aug 28, 2015
BACKGROUND: There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). Howev...
Fuzzy association rule mining and classification for the prediction of malaria in South Korea.
BMC medical informatics and decision making
Jun 18, 2015
BACKGROUND: Malaria is the world's most prevalent vector-borne disease. Accurate prediction of malaria outbreaks may lead to public health interventions that mitigate disease morbidity and mortality.
Artificial intelligence (AI) in point-of-care testing.
Clinica chimica acta; international journal of clinical chemistry
Jun 15, 2025
The integration of artificial intelligence (AI) into point-of-care testing (POCT) represents a transformative leap in modern healthcare, addressing critical challenges in diagnostic accuracy, workflow efficiency, and equitable access. While POCT has ...
Enhanced slime mould algorithm with chaotic and orthogonal optimization-based learning for improved severity prediction accuracy in malaria patient outcomes.
Computers in biology and medicine
Jun 1, 2025
Malaria remains a critical health challenge in developing countries, particularly in Africa, where it disproportionately affects vulnerable populations. Accurate malaria severity prediction is important for proper treatment and improved patient survi...
MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.
Journal of travel medicine
Dec 10, 2024
BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence...
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