Early prediction of acute kidney injury using machine learning algorithms
The application of machine learning algorithms in the medical sector is gaining increased attention in the last few decades. Thus, the main aim of this manuscript is to compare the performance of well-known machine learning (ML) algorithms to a problem in the domain of medical diagnosis and analyze...
| Main Authors: | Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Dzaharudin, Fatimah, Mat Ralib, Azrina, Md Nor, Norzaliza, Yahya, Norzariyah |
|---|---|
| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
2018
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/66159/ http://irep.iium.edu.my/66159/2/Video%20Conference%20APAN%2046%20-%20IIUM.pdf http://irep.iium.edu.my/66159/1/APAN-Presentation-Final-6Aug2018-1%20%281%29.pdf |
Similar Items
Model comparison of estimated glomerular filtration rate for
acute kidney injury in intensive care unit
by: Dzaharudin, Fatimah, et al.
Published: (2020)
by: Dzaharudin, Fatimah, et al.
Published: (2020)
Predictor of early diagnosis, diagnosis, or progression of acute kidney injury
by: Md Ralib, Azrina, et al.
Published: (2011)
by: Md Ralib, Azrina, et al.
Published: (2011)
Urine output in diagnosing acute kidney injury and predicting mortality
by: Md Ralib, Azrina, et al.
Published: (2015)
by: Md Ralib, Azrina, et al.
Published: (2015)
Biomarkers of acute kidney injury in the intensive care unit
by: Md Ralib, Azrina
Published: (2014)
by: Md Ralib, Azrina
Published: (2014)
Model comparison of estimated glomerular filtration rate for acute kidney injury in intensive care unit
by: Fatimah, Dzaharudin, et al.
Published: (2020)
by: Fatimah, Dzaharudin, et al.
Published: (2020)
Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury
by: Penny-Dimri, J.C., et al.
Published: (2021)
by: Penny-Dimri, J.C., et al.
Published: (2021)
The utility of biomarker excretion rates in acute kidney injury
by: Md Ralib, Azrina, et al.
Published: (2011)
by: Md Ralib, Azrina, et al.
Published: (2011)
The impact of fluid overload on mortality and acute kidney injury
by: Md Ralib, Azrina, et al.
Published: (2013)
by: Md Ralib, Azrina, et al.
Published: (2013)
Transient Acute Kidney Injury (AKI) is common following significant kidney hypoperfusion
by: Md Ralib, Azrina, et al.
Published: (2012)
by: Md Ralib, Azrina, et al.
Published: (2012)
New considerations in the design of clinical trials of acute
kidney injury
by: Md Ralib, Azrina, et al.
Published: (2011)
by: Md Ralib, Azrina, et al.
Published: (2011)
Predicting uniaxial compressive strength using Support Vector Machine algorithm
by: Zakaria, Hafedz, et al.
Published: (2019)
by: Zakaria, Hafedz, et al.
Published: (2019)
The urine output definition of acute kidney injury is too liberal
by: Md Ralib, Azrina, et al.
Published: (2013)
by: Md Ralib, Azrina, et al.
Published: (2013)
High-dose intravenous epoetin does not increase blood pressure in critically ill patients with acute kidney injury
by: Md Ralib, Azrina
Published: (2013)
by: Md Ralib, Azrina
Published: (2013)
Comparative performance of machine learning algorithms for cryptocurrency forecasting
by: Hitam, Nor Azizah, et al.
Published: (2018)
by: Hitam, Nor Azizah, et al.
Published: (2018)
Earlier measurement of biomarkers does not enhance detection of acute kidney injury following significant kidney hypoperfusion
by: Md Ralib, Azrina, et al.
Published: (2013)
by: Md Ralib, Azrina, et al.
Published: (2013)
The diagnostic and predictive value of plasma Cystatin C in acute kidney injury secondary to sepsis in the Intensive Care Unit
by: Ab. Rashid, Iqbalmunauwir, et al.
Published: (2018)
by: Ab. Rashid, Iqbalmunauwir, et al.
Published: (2018)
Acute kidney injury in a Malaysian Intensive Care Unit: incidence, risk factors and outcome
by: Md Ralib, Azrina, et al.
Published: (2015)
by: Md Ralib, Azrina, et al.
Published: (2015)
Prevalence of acute kidney injury and sepsis in a Malaysian intensive care setting
by: Md Ralib, Azrina, et al.
Published: (2017)
by: Md Ralib, Azrina, et al.
Published: (2017)
The clinical utility window for acute kidney injury biomarkers in the critically ill
by: Md Ralib, Azrina, et al.
Published: (2014)
by: Md Ralib, Azrina, et al.
Published: (2014)
Acute kidney injury in a Malaysian intensive care unit: assessment of incidence, risk factors and outcome
by: Md Ralib, Azrina, et al.
Published: (2015)
by: Md Ralib, Azrina, et al.
Published: (2015)
Acute kidney injury in Malaysian intensive care setting: incidences, risk factors and outcome
by: Md Ralib, Azrina, et al.
Published: (2018)
by: Md Ralib, Azrina, et al.
Published: (2018)
Prediction of acute kidney injury within 30 days of cardiac surgery
by: Ng, S., et al.
Published: (2014)
by: Ng, S., et al.
Published: (2014)
Combining creatinine and volume kinetics identifies missed cases of acute kidney injury following cardiac arrest
by: Pickering, John W., et al.
Published: (2013)
by: Pickering, John W., et al.
Published: (2013)
Test characteristics of urinary biomarkers depend on quantitation method in acute kidney injury
by: Md Ralib, Azrina, et al.
Published: (2012)
by: Md Ralib, Azrina, et al.
Published: (2012)
Impact of early postbariatric surgery acute kidney injury on long-term renal function
by: Nor Hanipah, Zubaidah, et al.
Published: (2018)
by: Nor Hanipah, Zubaidah, et al.
Published: (2018)
Acute kidney injury and the critically ill patient
by: Davies, Hugh, et al.
Published: (2012)
by: Davies, Hugh, et al.
Published: (2012)
Acute high-dose intravenous epoetin did not increase blood pressure in critically ill patients with acute kidney injury
by: Endre, Zoltan H., et al.
Published: (2011)
by: Endre, Zoltan H., et al.
Published: (2011)
Daily rainfall prediction using clonal selection algorithm
by: Noor Rodi, Nur Syazwani, et al.
Published: (2012)
by: Noor Rodi, Nur Syazwani, et al.
Published: (2012)
Machine learning algorithms for early predicting dropout student online learning
by: Dewi, Meta Amalya, et al.
Published: (2023)
by: Dewi, Meta Amalya, et al.
Published: (2023)
Plasma neutrophil gelatinase associated lipocalin diagnosed acute kidney injury in patients with systemic inflammatory disease and sepsis
by: Md Ralib, Azrina, et al.
Published: (2017)
by: Md Ralib, Azrina, et al.
Published: (2017)
Immune network algorithm in monthly streamflow prediction at Johor river
by: Mat Ali, Nur Izzah, et al.
Published: (2014)
by: Mat Ali, Nur Izzah, et al.
Published: (2014)
Immune network algorithm in monthly streamflow prediction at Johor river
by: Mat Ali, Nur Izzah, et al.
Published: (2015)
by: Mat Ali, Nur Izzah, et al.
Published: (2015)
Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
by: Amri, A’inur A’fifah, et al.
Published: (2018)
by: Amri, A’inur A’fifah, et al.
Published: (2018)
Monthly rainfall prediction model of Peninsular Malaysia using clonal selection algorithm
by: Rodi, N.S.Noor, et al.
Published: (2018)
by: Rodi, N.S.Noor, et al.
Published: (2018)
Acute kidney injury (AKI) in the intensive care unit (ICU) of Hospital Tengku Ampuan Afzan Kuantan (HTAA): Incidence, risk factors and outcome
by: Md Ralib, Azrina, et al.
Published: (2014)
by: Md Ralib, Azrina, et al.
Published: (2014)
The application of cardiac and renal imaging in the assessment of acute kidney injury and chronic kidney disease
by: Mahmoud, Huda S.
Published: (2022)
by: Mahmoud, Huda S.
Published: (2022)
Improved particle swarm optimization by fast annealing algorithm
by: Bashath, Samar, et al.
Published: (2019)
by: Bashath, Samar, et al.
Published: (2019)
Effect of Tualang honey in acute kidney injury animal model
by: Hamad Mohamed, Zenab, et al.
Published: (2017)
by: Hamad Mohamed, Zenab, et al.
Published: (2017)
Remote effects of acute kidney injury in a porcine model
by: Gardner, David S., et al.
Published: (2016)
by: Gardner, David S., et al.
Published: (2016)
International criteria for acute kidney injury: advantages and remaining challenges
by: Selby, Nicholas M., et al.
Published: (2016)
by: Selby, Nicholas M., et al.
Published: (2016)
Similar Items
-
Model comparison of estimated glomerular filtration rate for
acute kidney injury in intensive care unit
by: Dzaharudin, Fatimah, et al.
Published: (2020) -
Predictor of early diagnosis, diagnosis, or progression of acute kidney injury
by: Md Ralib, Azrina, et al.
Published: (2011) -
Urine output in diagnosing acute kidney injury and predicting mortality
by: Md Ralib, Azrina, et al.
Published: (2015) -
Biomarkers of acute kidney injury in the intensive care unit
by: Md Ralib, Azrina
Published: (2014) -
Model comparison of estimated glomerular filtration rate for acute kidney injury in intensive care unit
by: Fatimah, Dzaharudin, et al.
Published: (2020)