AIMC Topic: 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
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...

Image analysis and machine learning for detecting malaria.

Translational research : the journal of laboratory and clinical medicine
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...

Spatiotemporal Bayesian networks for malaria prediction.

Artificial intelligence in medicine
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...

Web-Enabled Distributed Health-Care Framework for Automated Malaria Parasite Classification: an E-Health Approach.

Journal of medical systems
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
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
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
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
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
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
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.