Ignite Creation Date:
2025-12-25 @ 1:28 AM
Ignite Modification Date:
2025-12-28 @ 1:36 AM
Study NCT ID:
NCT06245694
Status:
RECRUITING
Last Update Posted:
2024-11-22
First Post:
2024-01-30
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Predictive and Advanced Analytics in Emergency Medicine - Neurological Deficits
Sponsor:
Medical University of Vienna
Organization:
Study Overview
Official Title:
Predictive and Advanced Analytics in Emergency Medicine - Neurological Deficits
Status:
RECRUITING
Status Verified Date:
2024-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
PAN-EM-NEURO
Brief Summary:
Future predictive modeling in emergency medicine will likely combine the use of a wide range of data points such as continuous documentation, monitoring using wearables, imaging, biomarkers, and real-time administrative data from all health care providers involved. Subsequent extensive data sets could feed advanced deep learning and neural network algorithms to accurately predict the risk of specific health conditions. Moreover, predictive analytics steers towards the development of clinical pathways that are adaptive and continuously updated, and in which healthcare decision-making is supported by sophisticated algorithms to provide the best course of action effectively and safely. The potential for predictive analytics to revolutionize many aspects of healthcare seems clear in the horizon. Information on the use in emergency medicine is scarce.
Aim of the study is to evaluate the performance of using routine-data to predict resource usage in emergency medicine using the commonly encountered symptom of acute neurologic deficit. As an outlook, this might serve as a prototype for other, similar projects using routine medical data for predictive analytics in emergency medicine.
Aim of the study is to evaluate the performance of using routine-data to predict resource usage in emergency medicine using the commonly encountered symptom of acute neurologic deficit. As an outlook, this might serve as a prototype for other, similar projects using routine medical data for predictive analytics in emergency medicine.
Detailed Description:
None
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: