AIMC Topic: Bangladesh

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Mathematical analysis and prediction of future outbreak of dengue on time-varying contact rate using machine learning approach.

Computers in biology and medicine Jun 4, 2024
This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of this disease. The model explores the patterns and behaviors of dengue fever in Bangladesh. Incorpora...
Humans Bangladesh Animals Dengue Machine Learning Disease Outbreaks Epidemiological Models
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Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.

PloS one May 31, 2024
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...
Female Pregnant People Adult Cross-Sectional Studies Young Adult Algorithms Bangladesh Retrospective Studies Health Surveys Humans Middle Aged Pregnancy Machine Learning Adolescent Malnutrition Nutritional Status
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The Rohingya refugee crisis in Bangladesh: assessing the impact on land use patterns and land surface temperature using machine learning.

Environmental monitoring and assessment May 18, 2024
Bangladesh, a third-world country with the seventh highest population density in the world, has always struggled to ensure its residents' basic needs. But in recent years, the country is going through a serious humanitarian and financial crisis that ...
Humans Refugees Temperature Machine Learning Bangladesh Environmental Monitoring Myanmar
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Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

Scientific reports Apr 30, 2024
COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effec...
Aged Young Adult Adult Female SARS-CoV-2 Anxiety Adolescent Bangladesh Male Middle Aged Machine Learning COVID-19 Humans
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Application of machine learning and multivariate approaches for assessing microplastic pollution and its associated risks in the urban outdoor environment of Bangladesh.

Journal of hazardous materials Apr 18, 2024
Microplastics (MPs) are an emerging global concern due to severe toxicological risks for ecosystems and public health. Therefore, this is the first study in Bangladesh to assess MP pollution and its associated risks for ecosystems and human health in...
Bangladesh Multivariate Analysis Environmental Pollution Microplastics Dust Environmental Monitoring Humans Risk Assessment Cities Machine Learning
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Empowering real-time flood impact assessment through the integration of machine learning and Google Earth Engine: a comprehensive approach.

Environmental science and pollution research international Apr 3, 2024
Floods cause substantial losses to life and property, especially in flood-prone regions like northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for effective flood management and decision-making. This research demonst...
Floods Machine Learning Humans Support Vector Machine Neural Networks, Computer Bangladesh
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Assessment of coastal vulnerability using integrated fuzzy analytical hierarchy process and geospatial technology for effective coastal management.

Environmental science and pollution research international Jun 30, 2023
The vulnerability of coastal regions to climate change is a growing global concern, particularly in Bangladesh, which is vulnerable to flooding and storm surges due to its low-lying coastal areas. In this study, we used the fuzzy analytical hierarchy...
Climate Change Bangladesh Fuzzy Logic Floods
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An investigation into epidemiological situations of COVID-19 with fuzzy K-means and K-prototype clustering methods.

Scientific reports Apr 17, 2023
The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and policy plans. The Fuzzy K-Means (FKM) and K-prototype algorithms were used for clustering, and various pe...
Humans Algorithms COVID-19 Cluster Analysis Fuzzy Logic Bangladesh
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Tea leaf disease detection and identification based on YOLOv7 (YOLO-T).

Scientific reports Apr 13, 2023
A reliable and accurate diagnosis and identification system is required to prevent and manage tea leaf diseases. Tea leaf diseases are detected manually, increasing time and affecting yield quality and productivity. This study aims to present an arti...
Artificial Intelligence Plant Leaves Tea Bangladesh
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Prediction of monthly dry days with machine learning algorithms: a case study in Northern Bangladesh.

Scientific reports Nov 16, 2022
Dry days at varied scale are an important topic in climate discussions. Prolonged dry days define a dry period. Dry days with a specific rainfall threshold may visualize a climate scenario of a locality. The variation of monthly dry days from station...
Bangladesh Support Vector Machine Machine Learning Linear Models Algorithms
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