Understanding Fijian health system challenges in the prevention of mother-to-child transmission of HIV services in the three tertiary hospitals in Fiji

Razzaq, Amina; Travaglia, Joanne; Raynes-Greenow, Camille; Alam, Neeloy Ashraful

doi:10.1080/09540121.2024.2331215

AIDS Care

2024

DOI: 10.1080/09540121.2024.2331215

|View full text |Cite

Understanding Fijian health system challenges in the prevention of mother-to-child transmission of HIV services in the three tertiary hospitals in Fiji

Amina Razzaq,

Joanne Travaglia,

Camille Raynes-Greenow

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Developing Machine Learning Application for Early Cardiovascular Disease (Cvd) Risk Detection in Fiji: A Design Science Approach

SHARMA,

LAL,

KUMAR

2024

Appl. Comput. Sci.

View full text Add to dashboard Cite

CVD (cardiovascular disease) has become a significant contributor to premature deaths for many years in Fiji. CVD's late detection also significantly impacts annual deaths and casualties. Currently, Fiji lacks diagnosis tools that would enable people to know their risk levels. In this paper, a machine learning mobile application was developed that can be easily accessible to the local population for early prediction of CVD risk. The design science approach was used to guide the development of the application. The design process involved identifying the problem and motivation, setting objectives, creating a machine-learning mobile application for medical record analysis, demonstrating the application to selected participants, evaluating its usability and the machine-learning model's performance, and communicating the findings. The results revealed that the application proposed in this paper is an effective tool for CVD prediction in Fiji.

show abstract

Developing Machine Learning Application for Early Cardiovascular Disease (Cvd) Risk Detection in Fiji: A Design Science Approach

SHARMA,

LAL,

KUMAR

2024

Appl. Comput. Sci.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Understanding Fijian health system challenges in the prevention of mother-to-child transmission of HIV services in the three tertiary hospitals in Fiji

Cited by 1 publication

References 25 publications

Developing Machine Learning Application for Early Cardiovascular Disease (Cvd) Risk Detection in Fiji: A Design Science Approach

Developing Machine Learning Application for Early Cardiovascular Disease (Cvd) Risk Detection in Fiji: A Design Science Approach

Contact Info

Product

Resources

About