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World Health Organization

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A model for integrating palliative care into Eastern Mediterranean health systems with a primary care approach.

BMC palliative care
BACKGROUND AND AIMS: Palliative care in the Eastern Mediterranean Region (EMR) faces challenges despite the high number of patients in need. To provide accessible, affordable, and timely services, it is crucial to adopt a suitable care model. World h...

Vaccination hesitancy: agreement between WHO and ChatGPT-4.0 or Gemini Advanced.

Annali di igiene : medicina preventiva e di comunita
BACKGROUND: An increasing number of individuals use online Artificial Intelligence (AI) - based chatbots to retrieve information on health-related topics. This study aims to evaluate the accuracy in answering vaccine-related answers of the currently ...

The Evolving Regulatory Paradigm of AI in MedTech: A Review of Perspectives and Where We Are Today.

Therapeutic innovation & regulatory science
Artificial intelligence (AI)-enabled technologies in the MedTech sector hold the promise to transform healthcare delivery by improving access, quality, and outcomes. As the regulatory contours of these technologies are being defined, there is a notab...

Tanzania's and Germany's Digital Health Strategies and Their Consistency With the World Health Organization's Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis.

Journal of medical Internet research
BACKGROUND: In recent years, the fast-paced adoption of digital health (DH) technologies has transformed health care delivery. However, this rapid evolution has also led to challenges such as uncoordinated development and information silos, impeding ...

Predicting Schistosomiasis Intensity in Africa: A Machine Learning Approach to Evaluate the Progress of WHO Roadmap 2030.

The American journal of tropical medicine and hygiene
The World Health Organization (WHO) 2030 Roadmap aims to eliminate schistosomiasis as a public health issue, targeting reductions in the heavy intensity of infections. Previous studies, however, have predominantly used prevalence as the primary indic...

Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network.

The British journal of radiology
OBJECTIVES: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the valu...

Machine Learning-based World Health Organization Disability Assessment Schedule for persons with Parkinson's disease.

Parkinsonism & related disorders
INTRODUCTION: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known measure to assess disability in persons with Parkinson's disease (PD). The purpose of this study was to develop a short form of the WHODAS 2.0...

A comparative study on TB incidence and HIVTB coinfection using machine learning models on WHO global TB dataset.

Scientific reports
Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a significant global public health threat. HIV co-infection significantly increases the risk of active TB recurrence and prolongs medical treatment for tuberc...