AIMC Topic: Developing Countries

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The impact of austerity on children: Uncovering effect heterogeneity by political, economic, and family factors in low- and middle-income countries.

Social science research
Which children are most vulnerable when their government imposes austerity? Research tends to focus on either the political-economic level or the family level. Using a sample of nearly two million children in 67 countries, this study synthesizes theo...

The Impact of the COVID-19 Pandemic on Stock Market Performance in G20 Countries: Evidence from Long Short-Term Memory with a Recurrent Neural Network Approach.

Big data
In light of developing and industrialized nations, the G20 economies account for a whopping two-thirds of the world's population and are the largest economies globally. Public emergencies have occasionally arisen due to the rapid spread of COVID-19 g...

Artificial Intelligence inspired methods for the allocation of common goods and services.

PloS one
The debate over the optimal way of allocating societal surplus (i.e. products and services) has been raging, in one form or another, practically forever; following the collapse of the Soviet Union in 1991, the market has taken the lead vs the public ...

Multivariate random forest prediction of poverty and malnutrition prevalence.

PloS one
Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies' programming. However, state of the art models ofte...

Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BMC pregnancy and childbirth
BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, ad...

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis.

PloS one
In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, partic...

Right population, right resources, right algorithm: Using machine learning efficiently and effectively in surgical systems where data are a limited resource.

Surgery
There is a growing interest in using machine learning algorithms to support surgical care, diagnostics, and public health surveillance in low- and middle-income countries. From our own experience and the literature, we share several lessons for devel...

Comparing machine learning with case-control models to identify confirmed dengue cases.

PLoS neglected tropical diseases
In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have appli...