Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Use of Wearables to Detect Infections in Kidney Transplant Recipients

Institute for Clinical and Experimental Medicine · 2024
ClinicalTrials.gov · Datasets · License: Public Domain · 2024
Open Source ↗
infectionkidney-transplantationmachine-learning
The goal of this observational study is to develop a machine learning algorithm for early detection of infections in kidney transplant recipients using data recorded by wearable digital health technologies. The main questions it aims to answer are: 1. What are the biometric data pattern changes in impending infections? 2. What accuracy the machine learning algorithm can achieve? Participants will be given/use their own wearable device that will record biometric data. Any infection event will be recorded and an algorithm will be trained to recognize changes in biometric data preceding symptomatic infection.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1164629
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive