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101
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…</p><h3>Conclusions</h3><p dir="ltr">This scoping review provides an overview of recent studies based on machine learning models used to diagnose patients with BD regardless of their demographics or if they were compared to patients with psychiatric diagnoses. …”
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102
Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter
Published 2020“…The recent advancement in synthetic aperture radar (SAR) technology has enabled high-resolution imaging capability that calls for efficient speckle filtering algorithms to preprocess radar imagery. …”
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103
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
Published 2023“…Hence, in this paper, we survey the key studies that are published between 2014 and 2022, showcasing the different machine learning algorithms researchers have used to segment the liver, hepatic tumors, and hepatic-vasculature structures. …”
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104
Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review
Published 2023“…<div><p>Internet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of service (DDoS) attacks, intrusions, malwares, authentication problems or other fatal attacks. …”
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105
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…Therefore, it is necessary to detect fake job postings to get rid of online job scams. In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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106
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
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107
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108
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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doctoralThesis -
109
Modular-width
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110
Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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111
Just-in-time defect prediction for mobile applications: using shallow or deep learning?
Published 2023“…Traditional machine learning-based defect prediction models have been built since the early 2000s, and recently, deep learning-based models have been designed and implemented. …”
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112
Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation
Published 2024“…In this study, we have adopted a cycle consistent generative adversarial network (CycleGAN)-based approach for 3T MRI to 7T MRI translation, and vice versa, using a recently published dataset of paired T1-weighted MR images collected at 3T and 7T from a total of ten subjects. …”
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113
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Published 2023“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
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114
An efficient cache replacement strategy for the hybrid cache consistency approach
Published 2010“…Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. …”
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115
A low degree vertex elimination with high degree vertex selection heuristic for strongly connected dominating and absorbent sets in wireless Ad-Hoc networks. (c2011)
Published 2016“…Experimental results show that our approach outperforms all previously known algorithms for the SCDAS problem.…”
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116
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On the complexity of various parameterizations of common induced subgraph isomorphism
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118
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”