Exploring Hyper-Parameters and Feature Selection for Predicting Non-Communicable Chronic Disease Using Stacking Classifier
Non-communicable disease, especially chronic disease, is the most common factor of
complication of deteriorating physical health and the state of one's mind. It is also a …
complication of deteriorating physical health and the state of one's mind. It is also a …
An adaptive multi-class imbalanced classification framework based on ensemble methods and deep network
Data imbalance is one of the most difficult problems in machine learning. The improved
ensemble learning model is a promising solution to mitigate this challenge. In this paper, an …
ensemble learning model is a promising solution to mitigate this challenge. In this paper, an …
Ultrasensitive detection of vital biomolecules based on a multi-purpose BioMEMS for Point of care testing: digoxin measurement as a case study
Rapid and label-free detection of very low concentrations of biomarkers in disease
diagnosis or therapeutic drug monitoring is essential to prevent disease progression in Point …
diagnosis or therapeutic drug monitoring is essential to prevent disease progression in Point …
Early Prediction of Regional Red Needle Cast Outbreaks Using Climatic Data Trends and Satellite-Derived Observations
Red needle cast (RNC), mainly caused by Phytophthora pluvialis, is a very damaging
disease of the widely grown species radiata pine within New Zealand. Using a combination …
disease of the widely grown species radiata pine within New Zealand. Using a combination …
A clustering-based adaptive undersampling ensemble method for highly unbalanced data classification
The class imbalance issue is prevalent in various practical classification tasks. A high
unbalanced rate will significantly decrease the classification performance of unbalanced …
unbalanced rate will significantly decrease the classification performance of unbalanced …
Early Detection of Myrtle Rust on Pōhutukawa Using Indices Derived from Hyperspectral and Thermal Imagery
Myrtle rust is a very damaging disease, caused by the fungus Austropuccinia psidii, which
has recently arrived in New Zealand and threatens the iconic tree species pōhutukawa …
has recently arrived in New Zealand and threatens the iconic tree species pōhutukawa …
[PDF][PDF] Enhancing Prediction Accuracy in Gastric Cancer Using High-Confidence Machine Learning Models for Class Imbalance
D Jamil… - Journal of Advances …, 2023 - pdfs.semanticscholar.org
Gastric Cancer (GC) diagnosis and prognosis present significant challenges in the clinical
industry. To address the issue of low prediction accuracy resulting from imbalanced positive …
industry. To address the issue of low prediction accuracy resulting from imbalanced positive …
Machine learning model for prediction of malaria in low and high endemic areas of Tanzania
M Mariki - 2023 - dspace.nm-aist.ac.tz
Presumptive treatment and self-medication with anti-malaria drugs is a common practice in
most limited resource settings that hinders proper management of malaria. However, these …
most limited resource settings that hinders proper management of malaria. However, these …
Parallel Time-Sensor Attention for Electronic Health Record Classification
R DeVries, MLZ Mendoza, O Winther - openreview.net
When working with electronic health records (EHR), it is critical for deep learning (DL)
models to achieve both high performance and explainability. Here we present the Parallel …
models to achieve both high performance and explainability. Here we present the Parallel …