Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.7K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.7K
Methods Of Healthcare Delivery System01:26

Methods Of Healthcare Delivery System

3.4K
At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is...
3.4K
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

894
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
894
Primary Healthcare Services01:30

Primary Healthcare Services

1.5K
Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
In 1978, international leaders convened in Alma-Ata, Kazakhstan, for what would be a pivotal event in global health. The Alma-Ata Declaration was the first to call...
1.5K
International Nursing Organizations II01:28

International Nursing Organizations II

1.1K
The World Health Organization (WHO) is a specialized agency of the United Nations based in Geneva. The WHO has many initiatives that center around health. Primarily, they lead global efforts to expand universal health coverage using science-based policies and programs. They are also responsible for shaping health research agendas and developing norms and standards.
The WHO provides expert team support, including funding, vaccines, testing, and treatment tools at the country level to fight...
1.1K
Classification of Illness01:17

Classification of Illness

7.7K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Disinvestment in Global Health Threatens Global Security and Children's Health Everywhere.

Journal of the Pediatric Infectious Diseases Society·2026
Same author

Transcription Factors: A Promising Third-Generation Core Sensing Element for Developing Low-Cost, On-Site Rapid Detection Technologies for Food Contaminants.

Journal of agricultural and food chemistry·2026
Same author

Promise to Practice: Reimagining Artificial Intelligence for Equitable Global Health Impact.

Annals of global health·2026
Same author

Evaluating global health programmes targeting under-5 mortality: problems and recommendations.

BMJ global health·2026
Same author

From research to practice: a qualitative study examining the integration of telehealth-based suicide prevention in HIV care in Tanzania.

AIDS care·2026
Same author

Trump and RFK Jr have a new approach to global health: holding vulnerable people to ransom.

BMJ (Clinical research ed.)·2026

Related Experiment Video

Updated: Aug 19, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

660

Tracking financing for global common goods for health: A machine learning approach using natural language processing

Siddharth Dixit1, Wenhui Mao1, Kaci Kennedy McDade1

  • 1Center for Policy Impact in Global Health, Duke Global Health Institute, Duke University, Durham, NC, United States.

Frontiers in Public Health
|December 5, 2022
PubMed
Summary

Automating global health funding tracking with natural language processing (NLP) and machine learning (ML) is feasible. This approach accurately predicts funding for global common goods for health (CGH), improving efficiency.

Keywords:
classificationglobal common goods for healthmachine learningnatural language processingofficial development assistance

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

497
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.0K

Related Experiment Videos

Last Updated: Aug 19, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

660
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

497
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.0K

Area of Science:

  • Health economics
  • Computational linguistics
  • Machine learning applications in public health

Background:

  • Tracking global health funding is essential but traditionally time-consuming and labor-intensive.
  • Existing methods rely on manual data collection and classification, limiting scalability.
  • Need for efficient, automated systems to monitor financial flows for global health initiatives.

Purpose of the Study:

  • To develop and evaluate a framework for automating the tracking of global health spending.
  • To utilize natural language processing (NLP) and machine learning (ML) for classifying health projects.
  • To apply the global common goods for health (CGH) categorization framework.

Main Methods:

  • Utilized curated Official Development Assistance (ODA) disbursement data for global CGH (2013, 2015, 2017) for model training and validation.
  • Applied NLP techniques including stop word removal and lemmatization for text preprocessing.
  • Trained and tested four supervised ML algorithms: Random Forest (RF), XGBOOST, Support Vector Machine (SVM), and Multinomial Naïve Bayes (MNB).

Main Results:

  • The Random Forest (RF) model achieved the highest performance with a weighted average F1-score of 0.83.
  • The RF model accurately predicted total donor support for CGH projects ($2.24 billion over 3 years), closely matching human-coded estimates ($2.25 billion).
  • Predicted total funding for global CGH in 2019 was approximately $2.7 billion across 730 projects.

Conclusions:

  • NLP and ML provide a feasible and efficient method for classifying health projects into CGH categories.
  • Automated tracking of global health funding for CGH is achievable using publicly available data.
  • This framework enables routine and scalable monitoring of financial investments in global health priorities.