RESEARCH: AI-BASED MOBILE APP FOR PREDICTING HIV RISK IN VIETNAM

Trinh Duc Minh Nguyen
Hanoi – Amsterdam High School
Hanoi, Vietnam
ngtrinhducminh@gmail.com

Viet Tien Le
Faculty of Electronic Engineering
Hanoi University of Industry, HAUI
Hanoi, Vietnam
tienlv1@haui.edu.vn

Mai Hoang Long Nguyen
PT Automotive – AIS
FPT Software
Ho Chi Minh, Vietnam
longmh2@fpt.com

Phuc Hau Nguyen
Department of Information Technology
Thanh Do University
Hanoi, Vietnam
nphau@thanhdouni.edu.vn

Thi Phuoc Van Nguyen
Department of Information Technology
Thanh Do University
Hanoi, Vietnam
ntpvan@thanhdouni.edu.vn

Summary

This project is dedicated to crafting an advanced AI model and mobile application tailored to predict HIV risk among the Vietnamese population. To achieve this, the endeavour involves sourcing data from diverse countries to construct and assess various AI models, ultimately selecting the most effective one. The culmination of this effort will be an integrated mobile application designed to run on personal devices, ensuring both convenience and privacy for end-users.

The envisioned model and application represent a collaborative effort to empower individuals to assess their HIV risk discreetly and efficiently. The project aims to deliver a robust tool that contributes to proactive healthcare management by harmonising cutting-edge AI technology with an intuitive app interface. This initiative aligns with the broader goal of employing artificial intelligence to address public health challenges, with a particular focus on sensitive issues such as HIV risk assessment.

Illustration

data letter from The Demographic and Health Surveys (DHS) Program

By incorporating privacy-centric features and the convenience of a mobile platform, the project aims to enhance user engagement, fostering widespread adoption of this critical healthcare tool within the Vietnamese community. Ultimately, the project endeavours to play a pivotal role in early detection and prevention strategies, reinforcing the importance of proactive healthcare measures for public health in Vietnam.

Data sources

Accept letter

I recently received an email informing me that my paper titled “Two-layer smart system to predict HIV risk” has been accepted for ICST2024. The paper ID is #1571060871. It’s great news, although the specific category for the paper will be determined later.
Now, I have to make sure that my paper meets the formatting requirements provided by the conference. They gave me a link for guidance on this: http://www.ece.ul.ie/paper-submission.
I can check the reviews of the paper on their system through this link: https://edas.info/showPaper.php?m=1571060871.