AIMC Topic: World Health Organization

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Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

PloS one
BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of t...

Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries.

Globalization and health
The World Health Organization and other institutions are considering Artificial Intelligence (AI) as a technology that can potentially address some health system gaps, especially the reduction of global health inequalities in low- and middle-income c...

Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

International journal of computer assisted radiology and surgery
PURPOSE: The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision. The rarity of PNET often negatively affects the radiological application of deep learning algorith...

Machine Learning Model for Imbalanced Cholera Dataset in Tanzania.

TheScientificWorldJournal
Cholera epidemic remains a public threat throughout history, affecting vulnerable population living with unreliable water and substandard sanitary conditions. Various studies have observed that the occurrence of cholera has strong linkage with enviro...

Contrast enhancement is a prognostic factor in IDH1/2 mutant, but not in wild-type WHO grade II/III glioma as confirmed by machine learning.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Mutation of the isocitrate dehydrogenase (IDH) gene and co-deletion on chromosome 1p/19q is becoming increasingly relevant for the evaluation of clinical outcome in glioma. Among the imaging parameters, contrast enhancement (CE) in WHO II...

Humanitarian health computing using artificial intelligence and social media: A narrative literature review.

International journal of medical informatics
INTRODUCTION: According to the World Health Organization (WHO), over 130 million people are in constant need of humanitarian assistance due to natural disasters, disease outbreaks, and conflicts, among other factors. These health crises can compromis...