AIMC Topic: Delirium

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Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognostic accuracy in test datasets, but little is known about their embedding into clinical workflows. We implemented a random forest-based algorithm to iden...
Aged Aged, 80 and over Humans Male Machine Learning Female Algorithms Hospitalization Prospective Studies Models, Theoretical Electronic Health Records Workflow Delirium Middle Aged Risk Assessment ROC Curve
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Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients.

Studies in health technology and informatics Jun 23, 2020
Delirium is an acute mental disturbance that particularly occurs during hospital stay. Current clinical assessment instruments include the Delirium Observation Screening Scale (DOSS) or the Confusion Assessment Method (CAM). The aim of this work is t...
International Classification of Diseases Humans Machine Learning Delirium
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An Improvised Classification Model for Predicting Delirium.

Studies in health technology and informatics Aug 21, 2019
With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machine-learning techniques demonstrated their applications in healthcare to answer several questions, th...
Humans Machine Learning Logistic Models Delirium
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Is Regular Re-Training of a Predictive Delirium Model Necessary After Deployment in Routine Care?

Studies in health technology and informatics Jan 1, 2019
Adoption of electronic medical records in hospitals generates a large amount of data. Health care professionals can easily lose their sight on the important insights of the patients' clinical and medical history. Although machine learning algorithms ...
Hospitals Delirium Humans Machine Learning Algorithms Prognosis Electronic Health Records
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Information Adapted Machine Learning Models for Prediction in Clinical Workflow.

Studies in health technology and informatics Jan 1, 2019
BACKGROUND: In a database of electronic health records, the amount of available information varies widely between patients. In a real-time prediction scenario, a machine learning model may receive limited information for some patients.
Humans Machine Learning Databases, Factual Data Accuracy Electronic Health Records Workflow Delirium
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Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.

Studies in health technology and informatics Jan 1, 2018
The use of electronic health records for risk prediction models requires a sufficient quality of input data to ensure patient safety. The aim of our study was to evaluate the influence of incorrect administrative diabetes coding on the performance of...
Diabetes Mellitus Delirium Data Accuracy International Classification of Diseases Machine Learning Humans Algorithms Electronic Health Records
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On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care.

Studies in health technology and informatics Jan 1, 2018
Digitalisation of health care for the purpose of medical documentation lead to huge amounts of data, hence having an opportunity to derive knowledge and associations of different attributes recorded. Many health care events can be prevented when iden...
Delirium Documentation Humans Hospital Information Systems Prognosis Machine Learning Hospitalization
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Decreased Incidence of Postoperative Delirium in Robot-assisted Thoracoscopic Esophagectomy Compared With Open Transthoracic Esophagectomy.

Surgical laparoscopy, endoscopy & percutaneous techniques Dec 1, 2016
BACKGROUND: Postoperative delirium (POD) is one of messy complications related with increased mortality and hospital costs. Patients undergoing esophagectomy are more in danger of delirium than other kinds of surgeries. We investigated the impact of ...
Robotics Female Humans Incidence Aged Postoperative Complications Retrospective Studies Thoracoscopy Follow-Up Studies Delirium Republic of Korea Operative Time Length of Stay Propensity Score Thoracotomy Male Esophagectomy Esophageal Neoplasms
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[The influence of the sedation based on remifentanil analgesia on the occurrence of delirium in critically ill patients].

Zhonghua wei zhong bing ji jiu yi xue Oct 1, 2015
OBJECTIVE: To investigate the influence of the midazolam sedation based on remifentanil analgesia on the occurrence of delirium in critically ill patients in intensive care unit (ICU).
Midazolam Analgesia Remifentanil Kaplan-Meier Estimate Critical Illness Dexmedetomidine Humans Piperidines Hypnotics and Sedatives Intensive Care Units Pain Arterial Pressure Prospective Studies Respiration, Artificial Delirium
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