[HTML][HTML] An ensemble machine learning approach for predicting type-II diabetes mellitus based on lifestyle indicators
Abstract Machine Learning (ML) is a branch of artificial intelligence that allows computers to
learn without being explicitly programmed. ML has been widely used in healthcare to predict …
learn without being explicitly programmed. ML has been widely used in healthcare to predict …
MLP-PSO hybrid algorithm for heart disease prediction
A Al Bataineh, S Manacek - Journal of Personalized Medicine, 2022 - mdpi.com
Background: Machine Learning (ML) is becoming increasingly popular in healthcare,
particularly for improving the timing and accuracy of diagnosis. ML can provide disease …
particularly for improving the timing and accuracy of diagnosis. ML can provide disease …
[HTML][HTML] The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification
Breast cancer is one of the most common causes of death among women, and early
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
Breast tumor classification with enhanced transfer learning features and selection using chaotic map-based optimization
S Chakravarthy, B Nagarajan, VV Kumar… - International Journal of …, 2024 - Springer
Among women, breast cancer remains one of the most dominant cancer types. In the year
2022, around 2, 87,800 new cases were diagnosed, and 43,200 women faced mortality due …
2022, around 2, 87,800 new cases were diagnosed, and 43,200 women faced mortality due …
[HTML][HTML] A diagnostic analytics model for managing post-disaster symptoms of depression and anxiety among students using a novel data-driven optimization …
Prevalent mental disorders, such as depression and anxiety, commonly manifest in students
throughout the transition to early adulthood. Mental illnesses can significantly impact …
throughout the transition to early adulthood. Mental illnesses can significantly impact …
[HTML][HTML] A light gradient-boosting machine algorithm with tree-structured parzen estimator for breast cancer diagnosis
Breast cancer is a common and potentially life-threatening disease. Early and accurate
diagnosis of breast cancer is crucial for effective treatment and improved patient outcomes …
diagnosis of breast cancer is crucial for effective treatment and improved patient outcomes …
[HTML][HTML] A magnification-independent method for breast cancer classification using transfer learning
V Kumari, R Ghosh - Healthcare Analytics, 2023 - Elsevier
Breast cancer is the most common and diagnosed cancer among women worldwide.
Doctors use breast imaging reporting and data systems to classify breast density. This study …
Doctors use breast imaging reporting and data systems to classify breast density. This study …
A sampling-based stack framework for imbalanced learning in churn prediction
Churn prediction is gaining popularity in the research community as a powerful paradigm
that supports data-driven operational decisions. Datasets related to churn prediction are …
that supports data-driven operational decisions. Datasets related to churn prediction are …
RN-Autoencoder: Reduced Noise Autoencoder for classifying imbalanced cancer genomic data
Background In the current genomic era, gene expression datasets have become one of the
main tools utilized in cancer classification. Both curse of dimensionality and class imbalance …
main tools utilized in cancer classification. Both curse of dimensionality and class imbalance …
Statistical analysis of blood characteristics of COVID-19 patients and their survival or death prediction using machine learning algorithms
This study's main purpose is to provide helpful information using blood samples from COVID-
19 patients as a non-medical approach for helping healthcare systems during the pandemic …
19 patients as a non-medical approach for helping healthcare systems during the pandemic …