Cargando…

Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease

BACKGROUND: Acute kidney injury (AKI) is more likely to develop in the elderly admitted to the intensive care unit (ICU). Acute kidney disease (AKD) affects ∼45% of patients with AKI and increases short-term mortality. However, there are no studies on the prognosis of AKD in the elderly. METHODS: Da...

Descripción completa

Detalles Bibliográficos
Autores principales:	Li, Mingxia, Zhuang, Qinghe, Zhao, Shuangping, Huang, Li, Hu, Chenghuan, Zhang, Buyao, Hou, Qinlan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Taylor & Francis 2022
Materias:	Clinical Study
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9645285/ https://www.ncbi.nlm.nih.gov/pubmed/36341895 http://dx.doi.org/10.1080/0886022X.2022.2142139

Ejemplares similares

Exosomal microRNA-342-5p secreted from adipose-derived mesenchymal stem cells mitigates acute kidney injury in sepsis mice by inhibiting TLR9
por: Liu, Wei, et al.
Publicado: (2023)

Nomogram to predict the risk of septic acute kidney injury in the first 24 h of admission: an analysis of intensive care unit data
por: Deng, Fuxing, et al.
Publicado: (2020)

Sarcopenia and Mortality Risk of Patients with Sepsis: A Meta-Analysis
por: Liu, Wei, et al.
Publicado: (2022)

Factors Affecting Inpatient Mortality in Elderly People with Acute Kidney Injury
por: Khalil, Muhammad Abdul Mabood, et al.
Publicado: (2018)

Explainable machine learning model for predicting furosemide responsiveness in patients with oliguric acute kidney injury
por: Jiang, Meng, et al.
Publicado: (2023)

Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease
por: Zhang, Xiaohong, et al.
Publicado: (2022)

Correlation between neutrophil-to-lymphocyte ratio and contrast-induced acute kidney injury and the establishment of machine-learning-based predictive models
por: Zhou, Fangfang, et al.
Publicado: (2023)

The Agile Deployment of Machine Learning Models in Healthcare
por: Jackson, Stuart, et al.
Publicado: (2019)

Associations of low-carbohydrate with mortality in chronic kidney disease
por: Ren, Qidong, et al.
Publicado: (2023)

Interpretable machine learning prediction of all-cause mortality
por: Qiu, Wei, et al.
Publicado: (2022)

Machine learning in medicine: should the pursuit of enhanced interpretability be abandoned?
por: Yoon, Chang Ho, et al.
Publicado: (2022)

Predicting renal function recovery and short-term reversibility among acute kidney injury patients in the ICU: comparison of machine learning methods and conventional regression
por: Zhao, Xiujuan, et al.
Publicado: (2022)

Interpretable Machine Learning to Optimize Early In-Hospital Mortality Prediction for Elderly Patients with Sepsis: A Discovery Study
por: Ke, Xiaowei, et al.
Publicado: (2022)

Characteristics and risk factors for renal recovery after acute kidney injury in critically ill patients in cohorts of elderly and non-elderly: a multicenter retrospective cohort study
por: Zhao, Xiujuan, et al.
Publicado: (2023)

Development and internal validation of machine learning algorithms for end-stage renal disease risk prediction model of people with type 2 diabetes mellitus and diabetic kidney disease
por: Zou, Yutong, et al.
Publicado: (2022)

The Learning Curve of Gastric Intestinal Metaplasia Interpretation on the Images Obtained by Probe-Based Confocal Laser Endomicroscopy
por: Pittayanon, Rapat, et al.
Publicado: (2012)

C2 Fractures in the Elderly: Single-Center Evaluation of Risk Factors for Mortality
por: Chan, Hoi-Ying H., et al.
Publicado: (2019)

Effects of intensive blood pressure control on mortality and cardiorenal function in chronic kidney disease patients
por: Zhang, Yong, et al.
Publicado: (2021)

Pullout Strength Predictor: A Machine Learning Approach
por: Khatri, Ravi, et al.
Publicado: (2019)

Utilization of interpretable machine learning model to forecast the risk of major adverse kidney events in elderly patients in critical care
por: Wang, Lin, et al.
Publicado: (2023)

Application of interpretable machine learning for early prediction of prognosis in acute kidney injury
por: Hu, Chang, et al.
Publicado: (2022)

Serum uric acid is associated with chronic kidney disease in elderly Chinese patients with diabetes
por: Zhou, Qing, et al.
Publicado: (2023)

Effect of kidney disease on all-cause and cardiovascular mortality in patients undergoing coronary angiography
por: Li, Qiang, et al.
Publicado: (2023)

Surgical Management in Elderly Patients with Tuberculous Spondylodiscitis: Ten Year Mortality Audit Study
por: Kothari, Manish Kundanmal, et al.
Publicado: (2016)

Twenty-eight-day in-hospital mortality prediction for elderly patients with ischemic stroke in the intensive care unit: Interpretable machine learning models
por: Huang, Jian, et al.
Publicado: (2023)

Base-Rate Error in the Interpretation of Immunohistochemistry
por: Galloway, Malcolm
Publicado: (2011)

Association of acute kidney injury with frailty in elderly population: a systematic review and meta-analysis
por: Jiesisibieke, Zhu Liduzi, et al.
Publicado: (2019)

Different kidney function trajectory patterns before dialysis in elderly patients: clinical implications and outcomes
por: Santos, Josefina, et al.
Publicado: (2021)

The attributable mortality of sepsis for acute kidney injury: a propensity-matched analysis based on multicenter prospective cohort study
por: Jia, Hui-Miao, et al.
Publicado: (2023)

Problems in the deployment of machine-learned models in health care
por: Cohen, Joseph Paul, et al.
Publicado: (2021)

Deploying Machine Learning Techniques for Human Emotion Detection
por: Siam, Ali I., et al.
Publicado: (2022)

Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis
por: Cui, Chunyan, et al.
Publicado: (2020)

Obesity, acute kidney injury and mortality in patients with sepsis: a cohort analysis
por: Gameiro, Joana, et al.
Publicado: (2018)

Effect of hydrocortisone on the 28-day mortality of patients with septic acute kidney injury
por: Ying, Pan, et al.
Publicado: (2019)

Interpretable Machine Learning with Python
por: Masis, Serg
Publicado: (2021)

Interpretable machine learning for genomics
por: Watson, David S.
Publicado: (2021)

The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation
por: Michie, Susan, et al.
Publicado: (2017)

A New Time-Window Prediction Model For Traumatic Hemorrhagic Shock Based on Interpretable Machine Learning
por: Zhao, Yuzhuo, et al.
Publicado: (2022)

Intraoperative vasopressor use and early postoperative acute kidney injury in elderly patients undergoing elective noncardiac surgery
por: Ariyarathna, Dilshan, et al.
Publicado: (2022)

Retrospective analysis on incidence and risk factors of early onset acute kidney injury after lung transplantation and its association with mortality
por: Du, Wen-Wen, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_2gjuq97dmd9uluu5mafv43ltua