Efficient Pediatric Heart Transplant Predictions

Introduction: For youngsters with end-stage heart failure, an essential arrangement is a heart relocate; in any case, 1-year post-relocate mortality actually causes extraordinary concern. Augmenting beneficiary benefactor coordinating and improving patient results rely upon exact gauge of this mortality risk. Objectives: To predict 1-year demise risk in pediatric heart relocate patients Methods: This work utilizes the ICU heart relocate termination dataset. We offer a new system to work on figure accuracy by utilizing gathering procedures and upgraded include choice. The methodology incorporates a few classifiers for solid expectation and picks significant qualities in view of Chi-squared testing. Results: The outcomes show that with a precision of 100 percent, the recommended Casting a Voting Classifier — which mixes Helped Decision Tree and ExtraTree models — accomplishes an excellent presentation. Conclusion: This strategy presents a fast and precise method for assessing 1-year mortality risk, so giving specialists valuable data to assist with expanding beneficiary benefactor matching in pediatric heart transplantation and patient consideration.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-04
DOI
https://doi.org/10.52783/jisem.v10i15s.2492
Primary Topic
Transplantation: Methods and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient Pediatric Heart Transplant Predictions

Monelli Ayyavaraiah
1 links
Journal of Information Systems Engineering & Management
Transplantation: Methods and Outcomes
article

Efficient Pediatric Heart Transplant Predictions

Monelli Ayyavaraiah
article en

Abstract

Introduction: For youngsters with end-stage heart failure, an essential arrangement is a heart relocate; in any case, 1-year post-relocate mortality actually causes extraordinary concern. Augmenting beneficiary benefactor coordinating and improving patient results rely upon exact gauge of this mortality risk. Objectives: To predict 1-year demise risk in pediatric heart relocate patients Methods: This work utilizes the ICU heart relocate termination dataset. We offer a new system to work on figure accuracy by utilizing gathering procedures and upgraded include choice. The methodology incorporates a few classifiers for solid expectation and picks significant qualities in view of Chi-squared testing. Results: The outcomes show that with a precision of 100 percent, the recommended Casting a Voting Classifier — which mixes Helped Decision Tree and ExtraTree models — accomplishes an excellent presentation. Conclusion: This strategy presents a fast and precise method for assessing 1-year mortality risk, so giving specialists valuable data to assist with expanding beneficiary benefactor matching in pediatric heart transplantation and patient consideration.

Journal of Information Systems Engineering & ManagementVol. 10(15s)
Openalex Percentile: Top 93%
Transplantation: Methods and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Efficient Pediatric Heart Transplant Predictions — Monelli Ayyavaraiah · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS