Application of data mining techniques for medical data classification: a review
This paper investigates the existing practices and prospects of medical data classification
based on data mining techniques. It highlights major advanced classification approaches …
based on data mining techniques. It highlights major advanced classification approaches …
Multimodal gait recognition for neurodegenerative diseases
In recent years, single modality-based gait recognition has been extensively explored in the
analysis of medical images or other sensory data, and it is recognized that each of the …
analysis of medical images or other sensory data, and it is recognized that each of the …
A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1. 1) for spatial prediction of floods
D Tien Bui, ND Hoang - Geoscientific Model Development, 2017 - gmd.copernicus.org
In this study, a probabilistic model, named as BayGmmKda, is proposed for flood
susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian …
susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian …
Separation of geochemical anomalies from the sample data of unknown distribution population using Gaussian mixture model
Y Chen, W Wu - Computers & Geosciences, 2019 - Elsevier
The separation of geochemical anomalies from the sample data of unknown distribution
population is a great challenge, as it is difficult to determine the correct model for the …
population is a great challenge, as it is difficult to determine the correct model for the …
Perioperative predictions with interpretable latent representation
Given the risks and cost of hospitalization, there has been significant interest in exploiting
machine learning models to improve perioperative care. However, due to the high …
machine learning models to improve perioperative care. However, due to the high …
Aligning the achievement of SDGs with long-term sustainability and resilience: An OOBN modelling approach
This research utilizes an Object-Oriented Bayesian Network (OOBN) to model the
relationships between the Sustainable Development Goal (SDGs) and resilience and …
relationships between the Sustainable Development Goal (SDGs) and resilience and …
Deep LSTM enhancement for RUL prediction using Gaussian mixture models
M Sayah, D Guebli, Z Noureddine… - Automatic Control and …, 2021 - Springer
This paper introduces a new deep learning model for Remaining Useful Life (RUL)
prediction of complex industrial system components using Gaussian Mixture Models …
prediction of complex industrial system components using Gaussian Mixture Models …
[HTML][HTML] Interpreting clinical latent representations using autoencoders and probabilistic models
Electronic health records (EHRs) are a valuable data source that, in conjunction with deep
learning (DL) methods, have provided important outcomes in different domains, contributing …
learning (DL) methods, have provided important outcomes in different domains, contributing …
A novel classification method: A hybrid approach based on extension of the UTADIS with polynomial and PSO-GA algorithm
In this study, a new multi-criteria classification technique for nominal and ordinal groups is
developed by expanding the UTilites Additives DIScriminantes (UTADIS) method with a …
developed by expanding the UTilites Additives DIScriminantes (UTADIS) method with a …
Advanced CRITIC–GRA–GMM model with multiple restart simulation for assuaging decision uncertainty: An application to transport safety engineering for OECD …
Z Zhou, Y Zhang, Y Zhang, B Hou, Y Mei, P Wu… - Advanced Engineering …, 2024 - Elsevier
When dealing with multi-criteria decision-making (MCDM) activities in an uncertain
environment, one of the fundamental requirements of the methodology used is that it …
environment, one of the fundamental requirements of the methodology used is that it …