Handling imbalanced medical datasets: review of a decade of research
Abstract Machine learning and medical diagnostic studies often struggle with the issue of
class imbalance in medical datasets, complicating accurate disease prediction and …
class imbalance in medical datasets, complicating accurate disease prediction and …
A survey on unbalanced classification: How can evolutionary computation help?
Unbalanced classification is an essential machine learning task, which has attracted
widespread attention from both the academic and industrial communities due mainly to its …
widespread attention from both the academic and industrial communities due mainly to its …
Early prediction of diabetes using an ensemble of machine learning models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of
significant complications, including cardiovascular disease, kidney failure, diabetic …
significant complications, including cardiovascular disease, kidney failure, diabetic …
Solving the class imbalance problem using ensemble algorithm: application of screening for aortic dissection
L Liu, X Wu, S Li, Y Li, S Tan, Y Bai - BMC Medical Informatics and …, 2022 - Springer
Background Imbalance between positive and negative outcomes, a so-called class
imbalance, is a problem generally found in medical data. Despite various studies, class …
imbalance, is a problem generally found in medical data. Despite various studies, class …
Predicting student dropout and academic success
V Realinho, J Machado, L Baptista, MV Martins - Data, 2022 - mdpi.com
Higher education institutions record a significant amount of data about their students,
representing a considerable potential to generate information, knowledge, and monitoring …
representing a considerable potential to generate information, knowledge, and monitoring …
An efficient fraud detection framework with credit card imbalanced data in financial services
Credit card fraud has adversely impacted market economic order and has broken
stakeholders, financial entities, and consumers' trust and interest. Card fraud losses are …
stakeholders, financial entities, and consumers' trust and interest. Card fraud losses are …
Systematic review of class imbalance problems in manufacturing
Class imbalance (CI) is a well-known problem in data science. Nowadays, it is affecting the
data modeling of many of the real-world processes that are being digitized. The …
data modeling of many of the real-world processes that are being digitized. The …
[HTML][HTML] Healthcare fraud data mining methods: A look back and look ahead
Healthcare fraud is an expensive, white-collar crime in the United States, and it is not a
victimless crime. Costs associated with fraud are passed on to the population in the form of …
victimless crime. Costs associated with fraud are passed on to the population in the form of …
Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms
R Hassanzadeh, M Farhadian… - BMC medical research …, 2023 - Springer
Background Trauma is one of the most critical public health issues worldwide, leading to
death and disability and influencing all age groups. Therefore, there is great interest in …
death and disability and influencing all age groups. Therefore, there is great interest in …
[HTML][HTML] Ensemble based filter feature selection with harmonize particle swarm optimization and support vector machine for optimal cancer classification
Explosive increase of dataset features may intensify the complexity of medical data analysis
in deciding necessary treatment for the patient. In most cases, the accuracy of diagnosis …
in deciding necessary treatment for the patient. In most cases, the accuracy of diagnosis …