Hybrid approaches to optimization and machine learning methods: a systematic literature review
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
COVID-19 modeling: A review
L Cao, Q Liu - medRxiv, 2022 - medrxiv.org
The unprecedented and overwhelming SARS-CoV-2 virus and COVID-19 disease
significantly challenged our way of life, society and the economy. Many questions emerge, a …
significantly challenged our way of life, society and the economy. Many questions emerge, a …
PSO-ELPM: PSO with elite learning, enhanced parameter updating, and exponential mutation operator
Abstract Particle Swarm Optimization (PSO) has been widely used to solve optimization
problems. Although a large number of PSO variants have been proposed so far, they suffer …
problems. Although a large number of PSO variants have been proposed so far, they suffer …
[HTML][HTML] Uncertainty-driven ensembles of multi-scale deep architectures for image classification
The use of automatic systems for medical image classification has revolutionized the
diagnosis of a high number of diseases. These alternatives, which are usually based on …
diagnosis of a high number of diseases. These alternatives, which are usually based on …
A comparative analysis of meta-heuristic optimization algorithms for feature selection on ML-based classification of heart-related diseases
This study aims to use a machine learning (ML)-based enhanced diagnosis and survival
model to predict heart disease and survival in heart failure by combining the cuckoo search …
model to predict heart disease and survival in heart failure by combining the cuckoo search …
[HTML][HTML] Traditional machine learning models and bidirectional encoder representations from transformer (BERT)–based automatic classification of tweets about …
JA Benítez-Andrades, JM Alija-Pérez… - JMIR medical …, 2022 - medinform.jmir.org
Background Eating disorders affect an increasing number of people. Social networks
provide information that can help. Objective We aimed to find machine learning models …
provide information that can help. Objective We aimed to find machine learning models …
Sampling technique for noisy and borderline examples problem in imbalanced classification
Class imbalance Learning (CIL) is an important machine learning branch. Due to an
imbalanced dataset, the efficiency of the classifiers is impacted. Various under/oversampling …
imbalanced dataset, the efficiency of the classifiers is impacted. Various under/oversampling …
Metaheuristics based COVID-19 detection using medical images: A review
Many countries in the world have been facing the rapid spread of COVID-19 since February
2020. There is a dire need for efficient and cheap automated diagnosis systems that can …
2020. There is a dire need for efficient and cheap automated diagnosis systems that can …
Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
COVID-19 patient detection based on fusion of transfer learning and fuzzy ensemble models using CXR images
The COVID-19 pandemic has claimed the lives of millions of people and put a significant
strain on healthcare facilities. To combat this disease, it is necessary to monitor affected …
strain on healthcare facilities. To combat this disease, it is necessary to monitor affected …