Actively Recruiting

Age: 5Years - 18Years
All Genders
NCT07030998

Wearable Technology and Machine Learning for Early Detection and Risk Assessment of Unacceptable Toxicities in a Paediatric Oncology Cohort

Led by Murdoch Childrens Research Institute · Updated on 2025-11-17

150

Participants Needed

1

Research Sites

111 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

Data collection study to establish a predictive model of infection observed during childhood cancer therapy using data captured by wearable technology.

CONDITIONS

Official Title

Wearable Technology and Machine Learning for Early Detection and Risk Assessment of Unacceptable Toxicities in a Paediatric Oncology Cohort

Who Can Participate

Age: 5Years - 18Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Paediatric, adolescent or young adult diagnosis of cancer and receiving therapy placing them at risk of infection
  • Receiving cancer treatment at The Royal Children's Hospital
  • Patients aged 5-18 years at time of the eligibility screening
  • If aged < 16 years, parent or guardian able to provide consent
  • Own an iPhone 8 or later with up-to-date iOS
  • At least 10MB of iPhone storage available for the WEARABLES app and data collection
  • Willing and able to wear a wearable device during waking hours for 4 weeks
  • Consent to data being shared to the WEARABLES app (owned by the research team)
Not Eligible

You will not qualify if you...

  • Younger than 5 years of age
  • Under 16 years old without parent or guardian consent
  • Aged 16-18 and unable to provide consent
  • Did not consent to wearing the Apple Watch for 4 weeks

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

The Royal Children's Hospital

Parkville, Victoria, Australia

Actively Recruiting

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Research Team

L

Lane Collier

CONTACT

A

A/Prof Rachel Conyers

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

0

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