[HTML][HTML] MAgEC: Using non-homogeneous ensemble consensus for predicting drivers in unexpected mechanical ventilation
S Giampanis, A Mahajan, T Goldstein… - AMIA Summits on …, 2021 - ncbi.nlm.nih.gov
We conduct exploratory analysis of a novel algorithm called Model Agnostic Effect
Coefficients (MAgEC) for extracting clinical features of importance when assessing an …
Coefficients (MAgEC) for extracting clinical features of importance when assessing an …
Precisely predicting acute kidney injury with convolutional neural network based on electronic health record data
Y Wang, JP Bao, JQ Du, YF Li - arXiv preprint arXiv:2005.13171, 2020 - arxiv.org
The incidence of Acute Kidney Injury (AKI) commonly happens in the Intensive Care Unit
(ICU) patients, especially in the adults, which is an independent risk factor affecting short …
(ICU) patients, especially in the adults, which is an independent risk factor affecting short …
Modeling dynamic patients variables to renal failure in the intensive care unit using bayesian networks
Renal failure in the intensive care unit (ICU) is associated with high morbidity and mortality.
The Sequential Organ Failure Assessment (SOFA) score is applied in the ICU to track the …
The Sequential Organ Failure Assessment (SOFA) score is applied in the ICU to track the …
[图书][B] Development and Applications of Topological Data Analysis for Biomedicine
Y Skaf - 2023 - search.proquest.com
Thousands of clinical factors define a unique phenotype for each patient, all of which
contribute to the prognosis of that patient in different ways. This makes the problem of …
contribute to the prognosis of that patient in different ways. This makes the problem of …
Dynamic Detection of Delayed Cerebral Ischemia Using Machine Learning
Objective To develop a machine learning based tool, using routine vital signs, to assess
delayed cerebral ischemia (DCI) risk over time. Methods In this retrospective analysis …
delayed cerebral ischemia (DCI) risk over time. Methods In this retrospective analysis …
[PDF][PDF] 人工智能在急性肾损伤诊断中的价值和应用
李贵森， 吴昌为 - 中国血液净化, 2019 - cjbp.org.cn
急性肾损伤(acute kidney injury, AKI) 是临床常见且严重的问题. 根据改善全球肾脏病预后组织(
kidney disease: improving global outcomes, KDIGO) 的定义[1], 符合以下任一标准即为AKI …
kidney disease: improving global outcomes, KDIGO) 的定义[1], 符合以下任一标准即为AKI …
Artificial intelligence assisted early warning system for acute kidney injury driven by multi-center ICU database
Z Huang, S Huang, L Chen, WH Weng, L Wang, X Cui… - medRxiv, 2020 - medrxiv.org
Background To improve the performance of early acute kidney injury (AKI) prediction in
intensive care unit (ICU), we developed and externally validated machine learning …
intensive care unit (ICU), we developed and externally validated machine learning …
Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study
Early detection of patient deterioration is key to unlocking the potential for targeted
preventative care and improving patient outcomes. This protocol describes a workflow for …
preventative care and improving patient outcomes. This protocol describes a workflow for …
Deep-learning basierte Echtzeit-Vorhersage von akutem Nierenversagen nach kardiochirurgischen Eingriffen
N Rank - 2023 - refubium.fu-berlin.de
Die zunehmende Digitalisierung medizinischer Daten und die Fortschritte im Bereich der
künstlichen Intelligenz ermöglichen es, die enorme Menge an Daten, die während eines …
künstlichen Intelligenz ermöglichen es, die enorme Menge an Daten, die während eines …
Deep Risk Prediction and Embedding of Patient Data: Application to Acute Gastrointestinal Bleeding
DL Shung - 2022 - search.proquest.com
Acute gastrointestinal bleeding is a common and costly condition, accounting for over 2.2
million hospital days and 19.2 billion dollars of medical charges annually. Risk stratification …
million hospital days and 19.2 billion dollars of medical charges annually. Risk stratification …