A mobile app to improve detection of soil-transmitted infections and schistosomiasis

A Machine Learning-Based Mobile Application and Cloud Platform to Enable Accurate and Streamlined Surveillance of Soil-Transmitted Helminth Infection and Schistosomiasis

NIH-funded research Parasite Id, Corp. · NIH-10884444

This study is creating a handy mobile app that helps people count and identify certain parasites in stool samples, making it easier to track these infections even without internet access, so that public health efforts can be more effective.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionParasite Id, Corp. NIH-funded
Lab location1 site (Seattle, United States)
Project IDNIH-10884444 on NIH RePORTER

What this research studies

This research focuses on developing a mobile application that utilizes machine learning to identify and count eggs of soil-transmitted helminths and schistosomiasis from stool samples. The app will allow users to collect surveillance data even without an internet connection, which will then be uploaded to a cloud platform for analysis and visualization. By streamlining the testing process and improving the accuracy of results, this tool aims to enhance decision-making for public health interventions against these infections. The project combines expertise from global health researchers and data scientists to create a user-friendly solution for disease surveillance.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals living in areas where soil-transmitted helminths and schistosomiasis are prevalent.

Not a fit: Patients who do not reside in regions affected by these infections may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and timely detection of soil-transmitted infections, ultimately improving public health outcomes.

How similar studies have performed: While there have been advancements in machine learning applications for disease detection, this specific approach of integrating mobile technology with cloud-based data visualization is relatively novel.

Where this research is happening

Seattle, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.