Review of communication optimization methods in federated learning by YANG Zhikai, LIU Yaping, ZHANG Shuo, SUN Zhe, YAN Dingyu

“…Federated learning, as a distributed machine learning paradigm with privacy protection capabilities, exchanges model parameters through frequent communication between clients and parameter servers, training a joint model without the raw data leaving the local area. …”
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Feature selection in single-cell RNA sequencing data: a comprehensive evaluation by Petros Paplomatas, Konstantinos Lazaros, Georgios N. Dimitrakopoulos, Aristidis Vrahatis

“…We developed the GenesRanking package, which offers 20 techniques for dimensionality reduction, including filter-based and embedding machine learning–based methods. By integrating feature selection methods from both statistics and machine learning, we provide a robust framework for improving data interpretation. …”
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Learning-based page replacement scheme for efficient I/O processing by Hwajung Kim

“…Abstract Recent improvements in machine learning techniques offer new opportunities for addressing challenges across various domains. …”
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The Use of Neural Networks in the Diagnosis of Heart Failure Via the Analysis of Medical Data by Valentino Blanco, Aitana Iglesias

“…The three models, namely "k-means, support vector machine, and neural network," are extensively used classification methods in the domains of data mining and machine learning. These models have been applied to forecast cardiac disease, and their predictive performance has been evaluated and compared. …”
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Estimating the Torsional Capacity of Reinforced Concrete Beams Using ANFIS Models by Zhao Wenwu, Zeng Shaowu, Gong Guilin, Li Qiangqiang, Li Kexing

“…To overcome this limitation, accurate Machine Learning (𝑀𝐿) models might replace more sophisticated and computationally intensive models. …”
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Deteksi Cyberbullying dengan Mesin Pembelajaran Klasifikasi (Supervised Learning): Peluang dan Tantangan by Yudi Setiawan, Nur Ulfa Maulidevi, Kridanto Surendro

“…Penelitian deteksi pola dan karakteristik cyberbullying banyak dilakukan dengan berbagai metode, seperti dengan mengimplementasikan Machine Learning, Natural Language Processing (NLP), dan Sentiment Analysis yang memiliki variasi akurasi yang berbeda, dengan keunggulan dan kelemahan dari masing-masing metode. …”
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Innovative approaches in marketing for the development of the tourism industry by Yuliia Stasiuk, Andrii Kobchenko

“…The use of big data analytics, artificial intelligence, and machine learning allows tourism businesses to gain deep insights into customer preferences and behaviors. …”
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Leveraging an Enhanced CodeBERT-Based Model for Multiclass Software Defect Prediction via Defect Classification by Rida Ghafoor Hussain, Kin-Choong Yow, Marco Gori

“…In this context, machine learning-driven methods, especially those leveraging natural language models, have gained significant traction for developing effective techniques. …”
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Automatic Detection and Classification of Eye Diseases from Retinal Images Using Deep Learning: A Comprehensive Research on the ODIR Dataset by Asadi Srinivasulu, Clement Varaprasad Karu, G Sreenivasulu, Gayathri R

“…Existing approaches include machine learning, filtering-based, and model-based methods. …”
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Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching by Lukas Bischof, Stefan Teodoropol, Rudolf M. Füchslin, Kurt Stockinger

“…In this paper, we evaluate quantum machine learning algorithms for entity matching on a hand-crafted data set and compare them to similar classical algorithms. …”
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

“…This research investigates three approaches for classifying skin cancer images. (1) Utilizing three fine-tuned pre-trained networks (VGG19, ResNet18, and MobileNet_V2) as classifiers. (2) Employing three pre-trained networks (ResNet-18, VGG19, and MobileNet v2) as feature extractors in conjunction with four machine learning classifiers (SVM, DT, Naïve Bayes, and KNN). (3) Utilizing a combination of the aforementioned pre-trained networks as feature extractors in conjunction with same machine learning classifiers. …”
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Implementasi Algoritma Random Forest Untuk Menentukan Penerima Bantuan Raskin by Ilham Kurniawan, Duwi Cahya Putri Buani, Abdussomad Abdussomad, Widya Apriliah, Rizal Amegia Saputra

“…Tujuan penelitian ini adalah menemukan akurasi tertinggi di antara algoritma klasifikasi prediktif yang diusulkan penerima bantuan raskin menggunakan tools python machine learning dan di implementasikan melalui suatu website. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…Diseased people experience severe symptoms in more severe cases. such as shortness of breath, which can lead to respiratory failure and death. Machine learning techniques for detection and classification are commonly used in current medical diagnoses. …”
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Klasifikasi Penyakit Alzheimer Dari Scan Mri Otak Menggunakan Convnext by Yehezkiel Stephanus Austin, Haikal Irfano, Juan Young Christopher, Lintang Cahyaning Sukma, Octo Perdana Putra, Riyadh Ilham Ardhanto, Novanto Yudistira

“…Penanganan penyakit ini dapat dilakukan melalui deteksi dini untuk meningkatkan kualitas kehidupan pasien melalui perawatan medis yang efisien dan tepat waktu. Teknologi machine learning dan neural network dapat mendukung deteksi dini melalui penggunaan model ConvNeXt yang telah dilatih dengan metode transfer learning menggunakan bobot awal dari ImageNet, dan di-fine-tune untuk mengklasifikasikan empat tingkat keparahan Alzheimer berdasarkan hasil pemindaian MRI otak, yaitu Mild Demented, Moderate Demented, Non Demented, dan Very Mild Demented. …”
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A FUZZY LOGIC MODEL FOR HUMAN DISTRESS DETECTION by DIMPLE OGUNBIYI, IBRAHIM OGUNDOYIN, CALEB AKANBI

“…Existing research in distress detection arising from physical attacks focused mainly on the use of machine learning techniques. To extend research efforts, this study proposes an alternate approach using fuzzy logic. …”
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An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…Later, five state-of-the-art ensemble models for healthcare diagnosis were implemented along with a proposed ensemble machine learning model, KNN-XGBoost-SVM-Random Forest (KNN-X-SVM-R). …”
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Analisis Perbandingan Algoritma SVM, KNN, dan CNN untuk Klasifikasi Citra Cuaca by Mohammad Farid Naufal

“…KNN dan SVM merupakan algoritma klasifikasi dari Machine Learning sedangkan CNN merupakan algoritma klasifikasi dari Deep Neural Network. …”
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Cacao floral traits are shaped by the interaction of flower position with genotype by Seunghyun Lim, Insuck Baek, Seok Min Hong, Yoonjung Lee, Silvas Kirubakaran, Moon S. Kim, Lyndel W. Meinhardt, Sunchung Park, Ezekiel Ahn

“…These findings emphasize the phenotypic diversity of cacao flowers and demonstrate the potential of machine learning in genotype identification, offering valuable insights for breeding and cultivation strategies to enhance cacao productivity.…”
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Photovoltaic Farm Production Forecasting: Modified Metaheuristic Optimized Long Short-Term Memory-Based Networks Approach by Aleksandar Stojkovic, Bosko Nikolic, Miodrag Zivkovic, Nebojsa Bacanin

“…Finally, the applicability of the top-performance models was validated with tiny machine learning (TinyML).…”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). …”
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