An overview of fairness in clustering
Clustering algorithms are a class of unsupervised machine learning (ML) algorithms that
feature ubiquitously in modern data science, and play a key role in many learning-based …
feature ubiquitously in modern data science, and play a key role in many learning-based …
Classification and prediction of diabetes disease using machine learning paradigm
Background and objectives Diabetes is a chronic disease characterized by high blood
sugar. It may cause many complicated disease like stroke, kidney failure, heart attack, etc …
sugar. It may cause many complicated disease like stroke, kidney failure, heart attack, etc …
Big data analytics for preventive medicine
Medical data is one of the most rewarding and yet most complicated data to analyze. How
can healthcare providers use modern data analytics tools and technologies to analyze and …
can healthcare providers use modern data analytics tools and technologies to analyze and …
Performance analysis of classification algorithms on early detection of liver disease
The human liver is one of the major organs in the body and liver disease can cause many
problems in human life. Fast and accurate prediction of liver disease allows early and …
problems in human life. Fast and accurate prediction of liver disease allows early and …
Federated Random Forests can improve local performance of predictive models for various healthcare applications
Motivation Limited data access has hindered the field of precision medicine from exploring
its full potential, eg concerning machine learning and privacy and data protection rules. Our …
its full potential, eg concerning machine learning and privacy and data protection rules. Our …
Analyzing Quantum Feature Engineering and Balancing Strategies Effect on Liver Disease Classification
This research aims to improve the accuracy of liver disease classification using Quantum
Feature Engineering (QFE) and the Synthetic Minority Over-sampling Tech-nique and …
Feature Engineering (QFE) and the Synthetic Minority Over-sampling Tech-nique and …
[HTML][HTML] Computer-aided decision-making for predicting liver disease using PSO-based optimized SVM with feature selection
Using medical data mining models has been considered as a significant way to predict
diseases in recent years. In the field of healthcare, we face a large amount of data, and this …
diseases in recent years. In the field of healthcare, we face a large amount of data, and this …
KernelADASYN: Kernel based adaptive synthetic data generation for imbalanced learning
In imbalanced learning, most standard classification algorithms usually fail to properly
represent data distribution and provide unfavorable classification performance. More …
represent data distribution and provide unfavorable classification performance. More …
[PDF][PDF] A Comparative Analysis of Machine Learning Algorithms to Predict Liver Disease.
The liver is considered an essential organ in the human body. Liver disorders have risen
globally at an unprecedented pace due to unhealthy lifestyles and excessive alcohol …
globally at an unprecedented pace due to unhealthy lifestyles and excessive alcohol …
Randomized nonlinear one-class support vector machines with bounded loss function to detect of outliers for large scale IoT data
Exponential growth of large scale data industrial internet of things is evident due to the
enormous deployment of IoT data acquisition devices. Detection of unusual patterns from …
enormous deployment of IoT data acquisition devices. Detection of unusual patterns from …