Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #62
Submission information
Submission Number: 62
Submission ID: 150498
Submission UUID: 299b6cda-baca-4882-b02f-3d87ed4f96cd
Submission URI: /nci/ccdisymposium/abstract
Created: Mon, 09/01/2025 - 22:56
Completed: Mon, 09/01/2025 - 23:52
Changed: Mon, 09/01/2025 - 23:52
Remote IP address: 10.208.24.230
Submitted by: Anonymous
Language: English
Is draft: No
Abstract Title: | Digital Early Diagosis for Pediatric Brain Tumors: Sedation-Minimizing, Data-Driven Pathway |
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Abstract: | More than the tumor itself, the delayed diagnosis of pediatric brain tumor remains a global challenge. Through professional and public advice, the UK's HeadSmart awareness program could successfully reduce the median of total diagnostic interval (TDI) from 14.4 weeks in 2006 to 6.7 weeks in 2013. There are few low- and middle-income areas that still use similar structured techniques. But existing delays of low-grade tumors of 6-7 weeks highlights clinical and system-level issues. To improve the early-diagnosis route for pediatric brain tumors, we aim to design a system that combines age-stratified triage, sedation-minimizing imaging, mobile decision assistance, and real-world data collection. The system first defines red flag symptom threshold and imaging flow. This is further validated by the Parent Companion app for symptom tracking, and triage guidance. This significantly reduces TDI through better patient-system tracking, and promotes widespread adoption of digital tools to reduce manual burden of clinician’s automating tasks. The accuracy will be verified via vignette-based assessments and real-world discrepancy testing against standard head circumference measurements. This effort uses big data integration and digital health assessment to regulate and transform pediatric neuro-oncology diagnoses. This system aims to achieve data-driven early detection and scalable global childhood cancer therapy. |
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Presenting Author: | Rishika Sharma |
Institution: | Open Health Systems Laboratory (OHSL) |
Email Address: | rishika.sharma@ohsl.us |