Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications
about
A review of recent advances in data analytics for post-operative patient deterioration detection.Perioperative Acute Kidney Injury: Risk Factors and Predictive Strategies.MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery.Intelligent Perioperative System: Towards Real-time Big Data Analytics in Surgery Risk AssessmentTowards enhanced metabolomic data analysis of mass spectrometry image: Multivariate Curve Resolution and Machine LearningDelirium Prediction using Machine Learning Models on Preoperative Electronic Health Records Data
P2860
Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications
description
2016 nî lūn-bûn
@nan
2016 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Application of Machine Learnin ...... st Postoperative Complications
@ast
Application of Machine Learnin ...... st Postoperative Complications
@en
type
label
Application of Machine Learnin ...... st Postoperative Complications
@ast
Application of Machine Learnin ...... st Postoperative Complications
@en
prefLabel
Application of Machine Learnin ...... st Postoperative Complications
@ast
Application of Machine Learnin ...... st Postoperative Complications
@en
P2093
P2860
P1433
P1476
Application of Machine Learnin ...... st Postoperative Complications
@en
P2093
Bradley B Hupf
Panos Pardalos
Paul Thottakkara
Petar Momcilovic
Tezcan Ozrazgat-Baslanti
P2860
P304
P356
10.1371/JOURNAL.PONE.0155705
P407
P577
2016-05-27T00:00:00Z