Using Artificial Intelligence to Obtain More Evidence? Prediction of Length of Hospitalization in Pediatric Burn Patients
Background: It is not only important for counseling purposes and for healthcare management. This study investigates the prediction accuracy of an artificial intelligence (AI)-based approach and a linear model. The heuristic expecting 1 day of stay per percentage of total body surface area (TBSA) ser...
Saved in:
Main Authors: | Julia Elrod (Author), Christoph Mohr (Author), Ruben Wolff (Author), Michael Boettcher (Author), Konrad Reinshagen (Author), Pia Bartels (Author), German Burn Registry (Author), Ingo Koenigs (Author) |
---|---|
Format: | Book |
Published: |
Frontiers Media S.A.,
2021-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Combination of Side-Swing Flap With Negative-Pressure Wound Therapy Is Superior to Open Excision or Flap Alone in Children With Pilonidal Sinus-But at What Cost?
by: Deborah Dorth, et al.
Published: (2021) -
The Modified Heidelberg and the AI Appendicitis Score Are Superior to Current Scores in Predicting Appendicitis in Children: A Two-Center Cohort Study
by: Carolin Stiel, et al.
Published: (2020) -
The BAL-Score Almost Perfectly Predicts Testicular Torsion in Children: A Two-Center Cohort Study
by: Michaela Klinke, et al.
Published: (2020) -
Limits in Laparoscopic Partial Splenectomy in Children
by: Christian Tomuschat, et al.
Published: (2022) -
Health-Related Quality of Life and Mental Health of Parents of Children with Pediatric Abdominal Tumors
by: Kira Zierke, et al.
Published: (2024)