AIMC Topic: Malaria
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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
Apr 1, 2024
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
Mar 27, 2024
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
Nov 1, 2023
: 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
Jun 1, 2023
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
Apr 1, 2022
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
Jun 17, 2021
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
May 27, 2021
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...
Predictive analysis across spatial scales links zoonotic malaria to deforestation.
Proceedings. Biological sciences
Jan 16, 2019
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechani...
CAPi: Computational Model for Apicoplast Inhibitors Prediction Against Plasmodium Parasite.
Current computer-aided drug design
Nov 10, 2017
BACKGROUND: Discovery of apicoplast as a drug target offers a new direction in the development of novel anti-malarial compounds, especially against the drug-resistant strains. Drugs such as azithromycin were reported to block the apicoplast developme...
Artificial Neural Network Analysis of Pharmacokinetic and Toxicity Properties of Lead Molecules for Dengue Fever, Tuberculosis and Malaria.
Current computer-aided drug design
Jan 1, 2016
Poor pharmacokinetic and toxicity profiles are major reasons for the low rate of advancing lead drug candidates into efficacy studies. The In-silico prediction of primary pharmacokinetic and toxicity properties in the drug discovery and development p...
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