Search
Search Results
-
Ensemble learning for retinal disease recognition under limited resources
AbstractRetinal optical coherence tomography (OCT) images provide crucial insights into the health of the posterior ocular segment. Therefore, the...
-
A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer’s Disease using MRI Images
Recently, the early diagnosis of Alzheimer’s disease has gained major attention due to the growing prevalence of the disease and the resulting costs...
-
A novel atrial fibrillation automatic detection algorithm based on ensemble learning and multi-feature discrimination
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia disorder that necessitates long-time electrocardiogram (ECG) data for clinical diagnosis,...
-
Ensemble learning model for identifying the hallmark genes of NFκB/TNF signaling pathway in cancers
BackgroundThe nuclear factor kappa B (NFκB) regulatory pathways downstream of tumor necrosis factor (TNF) play a critical role in carcinogenesis....
-
Automatic classification of distal radius fracture using a two-stage ensemble deep learning framework
Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures....
-
Transfer learning–driven ensemble model for detection of diabetic retinopathy disease
In this study, we propose an ensemble model for the detection of diabetic retinopathy (DR) illness that is driven by transfer learning. Due to...
-
Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning
PurposeThis study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with...
-
A hybrid super ensemble learning model for the early-stage prediction of diabetes risk
Diabetes mellitus has become a rapidly growing chronic health problem worldwide. There has been a noticeable increase in diabetes cases in the last...
-
Architecting the metabolic reprogramming survival risk framework in LUAD through single-cell landscape analysis: three-stage ensemble learning with genetic algorithm optimization
Recent studies have increasingly revealed the connection between metabolic reprogramming and tumor progression. However, the specific impact of...
-
Strength of ensemble learning in automatic sleep stages classification using single-channel EEG and ECG signals
AbstractHealthy sleep plays an essential role in human daily life. Classification of sleep stages is a crucial tool for assisting physicians in...
-
Transfer learning-based ensemble convolutional neural network for accelerated diagnosis of foot fractures
The complex shape of the foot, consisting of 26 bones, variable ligaments, tendons, and muscles leads to misdiagnosis of foot fractures. Despite the...
-
Autism spectrum disorder recognition based on multi-view ensemble learning with multi-site fMRI
Autism spectrum disorders (ASD) is a neurodevelopmental disorder that causes repetitive stereotyped behavior and social difficulties, early diagnosis...
-
Ensemble Machine Learning Approaches Based on Molecular Descriptors and Graph Convolutional Networks for Predicting the Efflux Activities of MDR1 and BCRP Transporters
Multidrug resistance (MDR1) and breast cancer resistance protein (BCRP) play important roles in drug absorption and distribution. Computational...
-
Diagnosis of Respiratory Changes in Cystic Fibrosis Using a Soft Voting Ensemble with Bayesian Networks and Machine Learning Algorithms
PurposeAdvances in the treatment of cystic fibrosis (CF) have allowed patients to reach adulthood. The forced oscillation technique (FOT) is a new...
-
Ensemble classifier fostered detection of arrhythmia using ECG data
Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and function of the human heart. This is broadly employed in heart...
-
High-throughput precision MRI assessment with integrated stack-ensemble deep learning can enhance the preoperative prediction of prostate cancer Gleason grade
BackgroundTo develop and test a Prostate Imaging Stratification Risk (PRISK) tool for precisely assessing the International Society of Urological...
-
A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy
PurposeFast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rate...
-
Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set
Gain-of-function (GOF) variants give rise to increased/novel protein functions whereas loss-of-function (LOF) variants lead to diminished protein...
-
Disease Diagnosis Based on Improved Gray Wolf Optimization (IGWO) and Ensemble Classification
This paper introduces a simple strategy for diagnosing disease, which is called improved gray wolf optimization (IGWO) and ensemble classification....
-
DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data
Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce...
