Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms by Arindam Chaudhuri

“…The experiments are performed on both real and simulated datasets. It generates valuable information and produces overlapped clusters with different membership degrees. …”
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Machine learning and facial recognition for down syndrome detection: A comprehensive review by Khosro Rezaee

“…The review highlights the strengths and limitations of these methods, the importance of large and diverse datasets, and the need for models capable of handling variations in lighting, facial angles, and genetic diversity. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…This paper systematically reviews the growth of image classification technology, beginning with the introduction of commonly used datasets such as CIFAR-10, ImageNet, and MNIST, and exploring their impact on algorithm development. …”
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MAGInet based on deep learning for magnetic multi-parameter inversion by Wudi Wen, Yi Li, Zhongle Liu

“…The underlying principle of MAGInet’s multi-parameter inversion is to establish a learned mapping between the magnetic field signals and the multi-magnetic parameters of complex structures, leveraging extensive training datasets. In this study, simulation experiments are conducted, with training datasets generated via finite element magnetic field modeling, which are then utilized to fine-tune the MAGInet model. …”
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Integration of unpaired single cell omics data by deep transfer graph convolutional network. by Yulong Kan, Yunjing Qi, Zhongxiao Zhang, Xikeng Liang, Weihao Wang, Shuilin Jin

“…The rapid advance of large-scale atlas-level single cell RNA sequences and single-cell chromatin accessibility data provide extraordinary avenues to broad and deep insight into complex biological mechanism. Leveraging the datasets and transfering labels from scRNA-seq to scATAC-seq will empower the exploration of single-cell omics data. …”
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Evaluation of machine learning models for the prediction of Alzheimer's: In search of the best performance by Michael Cabanillas-Carbonell, Joselyn Zapata-Paulini

“…After processing and pooling the datasets, RF, SVM, and LR proved the best predictors, achieving 96% accuracy, precision, sensitivity, and F1 score. …”
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Secant Kumaraswamy Family of Distributions: Properties, Regression Model, and Applications by Salifu Nanga, Shei Baba Sayibu, Irene Dekomwine Angbing, Mubarika Alhassan, Abdul-Majeed Benson, Abdul Ghaniyyu Abubakari, Suleman Nasiru

“…The results show that the family of distributions can be used to model real datasets.…”
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Incremental Fuzzy Clustering Based on Feature Reduction by Yongli Liu, Yajun Zhang, Hao Chao

“…In the era of big data, more and more datasets are gradually beyond the application scope of traditional clustering algorithms because of their large scale and high dimensions. …”
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An Artificial Intelligence Approach for Verifying Persons by Employing the Deoxyribonucleic Acid (DNA) Nucleotides by Raid Rafi Omar Al-Nima, Marwa Mawfaq Mohamedsheet Al-Hatab, Maysaloon Abed Qasim

“…For all datasets, a low value of 0% is achieved for each of the false acceptance rate (FAR) and false rejection rate (FRR).…”
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Evaluating the Performance of Aluminum Oxide Nanoparticle-Modified Asphalt Binder and Modelling the Viscoelastic Properties by Using Artificial Neural Networks and Support Vector M... by Mustafa Alas, Sani Isah Abba, Shaban Ismael Albrka Ali, Abdur Rahim, Nur Izzi Md. Yusoff

“…Moreover, based on the statistical performance indicator, coefficient of determination (R2), it was observed that the ANN models for predicting G∗ and δ achieved a prediction accuracy of 0.989 and 0.911 while SVM models were able to achieve 0.984 and 0.929, respectively, considering the training datasets. On the other hand, it was noted that SVM models outperformed the ANN models in terms of a smaller gap between the results obtained from the training and testing datasets. …”
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A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection by Wasswa Shafik, Ali Tufail, Chandratilak Liyanage De Silva, Rosyzie Anna Awg Haji Mohd Apong

“…The experiments used six datasets, including PlantVillage, Turkey Disease, Plant Doc, Rice Disease, RoCole, and NLB datasets. …”
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Violence Detection From Industrial Surveillance Videos Using Deep Learning by Hamza Khan, Xiaohong Yuan, Letu Qingge, Kaushik Roy

“…We conducted experiments on violence detection across four datasets, comparing the performance of our model with convolutional CNN models. …”
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Nonrigid Registration of Monomodal MRI Using Linear Viscoelastic Model by Jian Yang, Yang Chen, Jingfan Fan, Songyuan Tang

“…To speed up the registration, an adaptive force is introduced according to the maximum displacement of each iteration. Both synthetic datasets and real datasets are used to evaluate the proposed method. …”
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Enhanced hunger games search algorithm that incorporates the marine predator optimization algorithm for optimal extraction of parameters in PEM fuel cells by Mohamed Issa, Mohamed Abd Elaziz, Sameh I. Selem

“…The effectiveness of HGS-MPA was validated on three commercial PEMFC datasets: 250-W stack, BCS 500-W, and NedStack PS6, using the Sum Squared Error (SSE) as the performance metric. …”
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Discrimination between the facial gestures of vocalising and non-vocalising lemurs and small apes using deep learning by Filippo Carugati, Olivier Friard, Elisa Protopapa, Camilla Mancassola, Emanuela Rabajoli, Chiara De Gregorio, Daria Valente, Valeria Ferrario, Walter Cristiano, Teresa Raimondi, Valeria Torti, Brice Lefaux, Longondraza Miaretsoa, Cristina Giacoma, Marco Gamba

“…However, manual inspection methods are only practical for small datasets. Deep learning techniques can help discriminate facial configurations associated with vocalisations over large datasets. …”
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Global Optimization Ensemble Model for Classification Methods by Hina Anwar, Usman Qamar, Abdul Wahab Muzaffar Qureshi

“…Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. …”
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Double Attention: An Optimization Method for the Self-Attention Mechanism Based on Human Attention by Zeyu Zhang, Bin Li, Chenyang Yan, Kengo Furuichi, Yuki Todo

“…Experimental results demonstrate the superior performance of our approaches across various benchmark datasets, validating their effectiveness. Furthermore, the method was applied to patient kidney datasets collected from hospitals for diabetes diagnosis, where they achieved high accuracy with significantly reduced computational demands. …”
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Percutaneous Dissolution of Gallstones using Methyl Tert-Butyl Ether by Johnson L Thistle, Bert T Petersen, Claire E Bender, Andrew J Leroy, Timothy M Ridgway

“…Percutaneous transhepatic catheter placement is a well established interventional radiology procedure and is the preferred route for MTBE administration. …”
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Giant Intraperitoneal Multiloculated Pseudocyst in a Male by Jacqueline Oxenberg

“…Reports of occurrences are mainly associated with long-term intraperitoneal catheter use, intraperitoneal catheter infections, or major pelvic surgery in females, although there are few reported incidences without prior trauma. …”
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Unexpected High Sensory Blockade during Continuous Spinal Anesthesiology (CSA) in an Elderly Patient by R. Ketelaars, A. P. Wolff

“…Fragmented doses of isobaric bupivacaine 0.5% were administered through a system consisting of a spinal catheter connected to an antimicrobial filter. After an uneventful surgical procedure, prior to removal of the catheter, this system was flushed with 10 mL of normal saline in order to try to prevent post-dural-puncture headache. …”
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