Cargando…

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

OBJECTIVE: To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN: Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS: 50,318 adult patients undergoing major surgery. MEASUREMENTS...

Descripción completa

Detalles Bibliográficos
Autores principales:	Thottakkara, Paul, Ozrazgat-Baslanti, Tezcan, Hupf, Bradley B., Rashidi, Parisa, Pardalos, Panos, Momcilovic, Petar, Bihorac, Azra
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2016
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883761/ https://www.ncbi.nlm.nih.gov/pubmed/27232332 http://dx.doi.org/10.1371/journal.pone.0155705

Ejemplares similares

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks
por: Shickel, Benjamin, et al.
Publicado: (2023)

Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU
por: Shickel, Benjamin, et al.
Publicado: (2021)

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning
por: Shickel, Benjamin, et al.
Publicado: (2019)

Multi-dimensional patient acuity estimation with longitudinal EHR tokenization and flexible transformer networks
por: Shickel, Benjamin, et al.
Publicado: (2022)

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform
por: Ren, Yuanfang, et al.
Publicado: (2022)

Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis
por: Adiyeke, Esra, et al.
Publicado: (2023)

Building an automated, machine learning-enabled platform for predicting post-operative complications
por: Balch, Jeremy A, et al.
Publicado: (2023)

Improving the Intensive Care Patient Experience With Virtual Reality—A Feasibility Study
por: Ong, Triton L., et al.
Publicado: (2020)

The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review
por: Cupka, Julie S, et al.
Publicado: (2022)

Machine Learning–Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review
por: Balch, Jeremy A, et al.
Publicado: (2023)

Association of Postoperative Undertriage to Hospital Wards With Mortality and Morbidity
por: Loftus, Tyler J., et al.
Publicado: (2021)

ICU Delirium-Prediction Models: A Systematic Review
por: Ruppert, Matthew M., et al.
Publicado: (2020)

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning
por: Davoudi, Anis, et al.
Publicado: (2019)

Cardiovascular and Renal Disease in Chronic Critical Illness
por: Loftus, Tyler J., et al.
Publicado: (2021)

Bilateral renal artery stenosis impacts postoperative complications after major vascular surgery()
por: Filiberto, Amanda C., et al.
Publicado: (2023)

EARLY DIFFERENTIATION BETWEEN SEPSIS AND STERILE INFLAMMATION VIA URINARY GENE SIGNATURES OF METABOLIC DYSREGULATION
por: Bandyopadhyay, Sabyasachi, et al.
Publicado: (2022)

Federated learning for preserving data privacy in collaborative healthcare research
por: Loftus, Tyler J, et al.
Publicado: (2022)

Methods for Phenotyping Adult Patients in Sepsis and Septic Shock: A Scoping Review
por: Li, Han, et al.
Publicado: (2022)

Clinical Considerations for Patients Experiencing Acute Kidney Injury Following Percutaneous Nephrolithotomy
por: Reich, Daniel A., et al.
Publicado: (2023)

Association of persistent acute kidney injury and renal recovery with mortality in hospitalised patients
por: Ozrazgat-Baslanti, Tezcan, et al.
Publicado: (2021)

Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics
por: Adhikari, Lasith, et al.
Publicado: (2019)

Physiologic signatures within six hours of hospitalization identify acute illness phenotypes
por: Ren, Yuanfang, et al.
Publicado: (2022)

Predictive Modeling for Readmission to Intensive Care: A Systematic Review
por: Ruppert, Matthew M., et al.
Publicado: (2023)

Uncertainty-aware deep learning in healthcare: A scoping review
por: Loftus, Tyler J., et al.
Publicado: (2022)

Insurance Status Is Associated with Treatment Allocation and Outcomes after Subarachnoid Hemorrhage
por: Hobson, Charles, et al.
Publicado: (2014)

Early Biomarker Signatures in Surgical Sepsis
por: Madushani, R.W.M.A., et al.
Publicado: (2022)

Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible
por: Loftus, Tyler J., et al.
Publicado: (2022)

Machine Learning Applications in Solid Organ Transplantation and Related Complications
por: Balch, Jeremy A., et al.
Publicado: (2021)

Discovery and Validation of Urinary Molecular Signature of Early Sepsis
por: Bandyopadhyay, Sabyasachi, et al.
Publicado: (2020)

Phenotype clustering in health care: A narrative review for clinicians
por: Loftus, Tyler J., et al.
Publicado: (2022)

Cardiovascular death and progression to end‐stage renal disease after major surgery in elderly patients
por: Lysak, N., et al.
Publicado: (2019)

Role of Wearable Accelerometer Devices in Delirium Studies: A Systematic Review
por: Davoudi, Anis, et al.
Publicado: (2019)

Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study
por: Fritz, Bradley A, et al.
Publicado: (2018)

Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
por: Davoudi, Anis, et al.
Publicado: (2022)

Opioid Safety and Concomitant Benzodiazepine Use in End-Stage Renal Disease Patients
por: Ruchi, Rupam, et al.
Publicado: (2019)

Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery
por: Loftus, Tyler J., et al.
Publicado: (2020)

What do the US advanced kidney disease patients want? Comprehensive pre-ESRD Patient Education (CPE) and choice of dialysis modality
por: Shukla, Ashutosh M., et al.
Publicado: (2019)

Successful Implementation of a Packed Red Blood Cell and Fresh Frozen Plasma Transfusion Protocol in the Surgical Intensive Care Unit
por: Szpila, Benjamin E., et al.
Publicado: (2015)

Sepsis and Critical Illness Research Center investigators: protocols and standard operating procedures for a prospective cohort study of sepsis in critically ill surgical patients
por: Loftus, Tyler J, et al.
Publicado: (2017)

Gamification for Machine Learning in Surgical Patient Engagement
por: Balch, Jeremy A., et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ehdshndodci0gs4hcuf39piiku