Linda Lapp

Phonelinda.lapp@strath.ac.uk

LT1206, Livingstone Tower

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Keywords

statistics
predictive modelling
perioperative medicine
cardiac surgery

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1 Conference contribution book

Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery
Lapp, L., Bouamrane, M-M., Kavanagh, K., Roper, M., Young, D. & Schraag, S., 30 May 2019, Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings. Wilk, S., ten Teije, A. & Riaño, D. (eds.). Cham: Springer, p. 376–385 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11526 LNAI).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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5 Citations (Scopus)

10 Downloads (Pure)

Code for: "Evaluation of Random Forest and Ensemble Methods at Predicting Complications Following Cardiac Surgery"
Lapp, L. (Creator) & Roper, M. (Supervisor), University of Strathclyde, 14 Jun 2022
DOI: 10.15129/9da23147-6be9-46f1-95be-6681ed2cc7e0, https://aime19.aimedicine.info/
Dataset
Exploratory Interviews with Cardiac Surgeons and Cardiac Anaesthetists
Lapp, L. (Creator) & Roper, M. (Supervisor), University of Strathclyde, 13 Jun 2022
DOI: 10.15129/fe89d27b-fa1e-4698-865e-5e4a2697b8ee
Dataset

Developing predictive models for postoperative complications in cardiac patients
Author: Lapp, L., 18 May 2018
Student thesis: Master's Thesis

Linda Lapp

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Dive into details

Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery

Code for: "Evaluation of Random Forest and Ensemble Methods at Predicting Complications Following Cardiac Surgery"

Exploratory Interviews with Cardiac Surgeons and Cardiac Anaesthetists

Developing predictive models for postoperative complications in cardiac patients

Linda Lapp

Personal profile

Keywords

Fingerprint

Network

Research output

Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery

Datasets

Code for: "Evaluation of Random Forest and Ensemble Methods at Predicting Complications Following Cardiac Surgery"

Exploratory Interviews with Cardiac Surgeons and Cardiac Anaesthetists

Thesis

Developing predictive models for postoperative complications in cardiac patients