Algorithmic fairness in computational medicine
Machine learning models are increasingly adopted for facilitating clinical decision-making.
However, recent research has shown that machine learning techniques may result in …
However, recent research has shown that machine learning techniques may result in …
MicroRNAs and epigenetics strategies to reverse breast cancer
MM Rahman, AC Brane, TO Tollefsbol - Cells, 2019 - mdpi.com
Breast cancer is a sporadic disease with genetic and epigenetic components. Genomic
instability in breast cancer leads to mutations, copy number variations, and genetic …
instability in breast cancer leads to mutations, copy number variations, and genetic …
[HTML][HTML] COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios
Abstract Background and Objective: The COVID-19 can cause severe pneumonia and is
estimated to have a high impact on the healthcare system. Early diagnosis is crucial for …
estimated to have a high impact on the healthcare system. Early diagnosis is crucial for …
COVID-19 cough classification using machine learning and global smartphone recordings
We present a machine learning based COVID-19 cough classifier which can discriminate
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …
Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning
Imbalanced data problems are prevalent in the real rotating machinery applications.
Traditional data-driven diagnosis methods fail to identify the fault condition effectively for …
Traditional data-driven diagnosis methods fail to identify the fault condition effectively for …
An empirical evaluation of sampling methods for the classification of imbalanced data
M Kim, KB Hwang - PLoS One, 2022 - journals.plos.org
In numerous classification problems, class distribution is not balanced. For example, positive
examples are rare in the fields of disease diagnosis and credit card fraud detection. General …
examples are rare in the fields of disease diagnosis and credit card fraud detection. General …
A Novel Ensemble Method for Imbalanced Data Learning: Bagging of Extrapolation‐SMOTE SVM
Q Wang, ZH Luo, JC Huang… - Computational …, 2017 - Wiley Online Library
Class imbalance ubiquitously exists in real life, which has attracted much interest from
various domains. Direct learning from imbalanced dataset may pose unsatisfying results …
various domains. Direct learning from imbalanced dataset may pose unsatisfying results …
[HTML][HTML] Understanding travel behavior adjustment under COVID-19
The outbreak and spreading of the COVID-19 pandemic have had a significant impact on
transportation system. By analyzing the impact of the pandemic on the transportation system …
transportation system. By analyzing the impact of the pandemic on the transportation system …
Radiomics-based method for predicting the glioma subtype as defined by tumor grade, IDH mutation, and 1p/19q codeletion
Simple Summary In 2016, the World Health Organization (WHO) recommended the
incorporation of molecular parameters, in addition to histology, for an optimal definition of …
incorporation of molecular parameters, in addition to histology, for an optimal definition of …
Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types
In the last decade, the widespread adoption of electronic health record documentation has
created huge opportunities for information mining. Natural language processing (NLP) …
created huge opportunities for information mining. Natural language processing (NLP) …