Similarity Measures of Pythagorean Neutrosophic Sets with Dependent Neutrosophic Components Between T and F by Mohana Krıshnaswamy, Jansi Rajan

“…Clustering plays an important role in data mining, pattern recognition and machine learning. This paper proposes Pythagorean neutrosophic clustering methods based on similarity measures between Pythagorean neutrosophic sets with T and F are dependent neutrosophic components [PN-Set]. …”
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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…Data-driven approaches, particularly those methods based on machine learning, are currently being used due to their ability to model complex degradation patterns without the need for explicit physical modeling. …”
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Automated Cough Analysis with Convolutional Recurrent Neural Network by Yiping Wang, Mustafaa Wahab, Tianqi Hong, Kyle Molinari, Gail M. Gauvreau, Ruth P. Cusack, Zhen Gao, Imran Satia, Qiyin Fang

“…These findings provide insights into the strengths and limitations of various algorithms, highlighting the potential of CRNNs in analyzing complex cough patterns. …”
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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…Abstract Machine learning (ML) algorithms have been widely applied across geosciences for tasks such as data conditioning, resolution enhancement, and image classification. …”
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Optimal Fuzzy Deep Neural Networks-Based Plant Disease Detection and Classification on UAV-Based Remote Sensed Data by M. Pajany, S. Venkatraman, U. Sakthi, M. Sujatha, Mohamad Khairi Ishak

“…At the primary level, the OFDNN-PDDC technique employs an improved ShuffleNetv2 model for learning complex and intrinsic feature patterns on the RS data. Besides, the OFDNN-PDDC technique utilizes a fuzzy restricted Boltzmann machine (FRBM) model to detect plant diseases. …”
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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Currently, numerous physical methods exist to evaluate and forecast blood cancer utilizing the microscopic health information of white blood cell (WBC) images that are stable for prediction and cause many deaths. Machine learning (ML) and deep learning (DL) have aided the classification and collection of patterns in data, foremost in the growth of AI methods employed in numerous haematology fields. …”
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Dementia Scale Score Classification Based on Daily Activities Using Multiple Sensors by Akira Minamisawa, Shogo Okada, Ken Inoue, Mami Noguchi

“…The experimental results show that a maximum accuracy of 0.871 was obtained with a linear support vector machine (SVM) model by fusing the door, location, and sleep features and by clustering activity patterns using the X-means algorithm.…”
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Evaluating textural descriptors for automated image classification of stony reefs in turbid temperate waters by Saulė Medelytė, Yuri Rzhanov, Andrius Šiaulys, Kim Lowell

“…Among these, the MRELBP (Median Robust Extended Local Binary Pattern) algorithm achieved the highest overall performance. …”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…These complementary attributes capture both predominant patterns and detailed texture information from magnetic resonance imaging (MRI) scans, facilitating thorough tumor characterization. …”
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Detecting and Analyzing Botnet Nodes via Advanced Graph Representation Learning Tools by Alfredo Cuzzocrea, Abderraouf Hafsaoui, Carmine Gallo

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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…A modern approach to enhancing the capabilities of NIDSs is the use of machine learning (ML) algorithms that predict attacks based on data. …”
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Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization by Hua Huang, Haiyan Shao, Yifan Wang, Lili Ge

“…By integrating data from TCGA and GEO cohorts, we developed a Disulfide-Related Prognostic Signature (DRPS) using ten machine learning algorithms. Single-cell RNA sequencing (scRNA-seq) elucidated the cell subtype-specific expression patterns of disulfide bond regulatory genes, while immune microenvironment and drug sensitivity analyses validated its clinical translational potential. qRT-PCR experiments confirmed differential expression patterns of core genes in bladder cancer cell lines. …”
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Klasifikasi Metode Data Mining untuk Prediksi Kelulusan Tepat Waktu Mahasiswa dengan Algoritma Naïve Bayes, Random Forest, Support Vector Machine (SVM) dan Artificial Neural Nerwor... by Satrio Junaidi, Rani Valicia Anggela, Delsi Kariman

“…The results of this study were obtained with the best algorithm accuracy in the support vector machine (SVM) algorithm is 0.94. …”
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Unsupervised learning analysis on the proteomes of Zika virus by Edgar E. Lara-Ramírez, Gildardo Rivera, Amanda Alejandra Oliva-Hernández, Virgilio Bocanegra-Garcia, Jesús Adrián López, Xianwu Guo

“…Results The four UL algorithms revealed specific host and geographical clustering patterns for ZIKV. …”
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Regulatory T cells and matrix-producing cancer associated fibroblasts contribute on the immune resistance and progression of prognosis related tumor subtypes in ccRCC by Chao Zhang, Yisu Song, Xiaobo Cui, Yina Wang, Jiang Liu, Zhouji Shen

“…The distinct activated transcription factor patterns were uncovered as well as the essential ligand-receptor pairs in the interactions among different cell subtypes, such as CXCL12-CXCR4 and COL6A2-SDC4. …”
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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…It benchmarks the performance of ten existing machine learning imputation algorithms against Flexible on real-world EHR datasets containing laboratory measurements. …”
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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…To accomplish this goal, we have proposed an integrated system which encompasses the use of machine learning (ML) algorithms. This hybrid model is aimed at linking various activities to VAK model of learning and hence place students in their various class learning preferences derived from their activities and the patterns created during the learning processes. …”
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Long-Range Wide Area Network Intrusion Detection at the Edge by Gonçalo Esteves, Filipe Fidalgo, Nuno Cruz, José Simão

“…This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN) algorithm, within an Intrusion Detection System (IDS) for LoRaWAN networks. …”
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