AIMC Topic: World Health Organization

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WHO global research priorities for traditional, complementary, and integrative (TCI) medicine: an international consensus and comparisons with LLMs.

Journal of global health
BACKGROUND: Traditional, complementary, and integrative (TCI) medicine is an essential component of health systems worldwide, especially in low- and middle-income countries. Despite its widespread use, existing research on the safety, efficacy, and i...

Potential of the World Health Organization's Skin NTDs App to Support and Improve the Detection of Skin-Related Neglected Tropical Diseases: Protocol for a Performance Evaluation and Feasibility Study in Senegal.

JMIR research protocols
BACKGROUND: The World Health Organization (WHO) roadmap aims to control, eliminate, or eradicate neglected tropical diseases (NTDs) by promoting innovation in prevention, diagnosis, and treatment. In this context, mobile health (mHealth) tools could ...

Chatbot-Based Version of a World Health Organization-Validated Intervention for Stress Management in Patients With Breast Cancer (Self-Help Plus): Protocol for a Pilot Feasibility Study.

JMIR research protocols
BACKGROUND: Emerging digital tools play an innovative and key role in supporting women's psychological well-being throughout the different stages and challenges of cancer. The development and adoption of digital interventions, including chatbots and ...

Should Digital Interventions for HIV Self-Testing Be Regulated with World Health Organization Prequalification?

JMIR mHealth and uHealth
HIV self-testing (HIVST) allows people to test for HIV outside traditional health facilities, but this presents challenges around pre- and posttest counseling, reporting results, and linking to care. Digital interventions for HIVST, a type of Softwar...

Evaluating the Performance of State-of-the-Art Artificial Intelligence Chatbots Based on the WHO Global Guidelines for the Prevention of Surgical Site Infection: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Surgical site infection (SSI) is the most prevalent type of health care-associated infection that leads to increased morbidity and mortality and a significant economic burden. Effective prevention of SSI relies on surgeons strictly follow...

Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.

BMC cancer
BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organization (WHO) grade 4 Central Nervous System (CNS) gliomas is highly relevant for prognostic stratification and personalized treatment.

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...

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 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...