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Malaria

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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.

MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.

Journal of travel medicine
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...

Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017.

The Lancet. Planetary health
BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogene...

A Bayesian convolutional neural network-based generalized linear model.

Biometrics
Convolutional neural networks (CNNs) provide flexible function approximations for a wide variety of applications when the input variables are in the form of images or spatial data. Although CNNs often outperform traditional statistical models in pred...

Efficacy of Pulse Methylprednisolone in Treatment of Acute Respiratory Distress Syndrome due to Malaria: A Randomized Controlled Clinical Trial.

The Journal of the Association of Physicians of India
: To study the efficacy of pulse methylprednisolone (MPS) therapy in patients with malaria-associated acute respiratory distress syndrome (ARDS). : The study was a randomized, single-blind, placebo-controlled trial with a total sample size of 44 pati...

An automated malaria cells detection from thin blood smear images using deep learning.

Tropical biomedicine
Timely and rapid diagnosis is crucial for faster and proper malaria treatment planning. Microscopic examination is the gold standard for malaria diagnosis, where hundreds of millions of blood films are examined annually. However, this method's effect...

The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: a longitudinal cohort study.

The Lancet. Planetary health
BACKGROUND: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and t...

Multi-stage malaria parasite recognition by deep learning.

GigaScience
MOTIVATION: Malaria, a mosquito-borne infectious disease affecting humans and other animals, is widespread in tropical and subtropical regions. Microscopy is the most common method for diagnosing the malaria parasite from stained blood smear samples....

On the Efficiency of Machine Learning Models in Malaria Prediction.

Studies in health technology and informatics
Malaria is still a real public health concern in Sub-Saharan African countries such as Senegal where it represents approximately 35% of the consultation activities in the hospitals. This is mainly due to the lack of appropriate medical care support a...