Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field by Zhikai Yu, Binghao Yang, Penghu Wei, Hang Xu, Yongzhi Shan, Xiaotong Fan, Huaqiang Zhang, Changming Wang, Jingjing Wang, Shan Yu, Guoguang Zhao

“…The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models, whereas the Naive Bayesian model necessitates the least amount of computational and storage space. …”
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Attention-enhanced corn disease diagnosis using few-shot learning and VGG16 by Ruchi Rani, Jayakrushna Sahoo, Sivaiah Bellamkonda, Sumit Kumar

“…With the advent of AI, Machine Learning and Deep Learning methods are used to detect and categorize plant diseases. …”
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Research on Road Adhesion Condition Identification Based on an Improved ALexNet Model by QiMing Wang, JinMing Xu, Tao Sun, ZhiChao Lv, GaoQiang Zong

“…Finally, the traditional machine learning and improved ALexNet model are compared, focusing on adaptability, prediction output, and error performance, among others. …”
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Dynamic Spatial–Temporal Graph Neural Network for Cooling Capacity Prediction in HVDC Systems by Hao Sun, Shaosen Li, Jianxiang Huang, Hao Li, Guanxin Jing, Ye Tao, Xincui Tian

“…The proposed method demonstrates superior performance over traditional machine learning and deep learning baselines on real-world cooling system data. …”
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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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CombinatorixPy: Advancing mixture descriptors for computational chemistry by Rahil Ashtari Mahini, Gerardo Casanola-Martin, Stephen Szwiec, Simone A. Ludwig, Bakhtiyor Rasulev

“…Quantitative Structure-Activity/Property Relationship (QSAR/QSPR) is a machine learning approach to predict chemical and physical properties of pure compounds; however, it has limited application in multi-component compounds. …”
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Adapting a style based generative adversarial network to create images depicting cleft lip deformity by Abdullah Hayajneh, Erchin Serpedin, Mohammad Shaqfeh, Graeme Glass, Mitchell A. Stotland

“…Abstract Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. …”
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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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miRNA-Disease Association Prediction with Collaborative Matrix Factorization by Zhen Shen, You-Hua Zhang, Kyungsook Han, Asoke K. Nandi, Barry Honig, De-Shuang Huang

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Analysis of Multidimensional Clinical and Physiological Data with Synolitical Graph Neural Networks by Mikhail Krivonosov, Tatiana Nazarenko, Vadim Ushakov, Daniil Vlasenko, Denis Zakharov, Shangbin Chen, Oleg Blyus, Alexey Zaikin

“…SGNNs are particularly good for addressing the challenges posed by high-dimensional datasets, particularly in healthcare, where traditional machine learning and Artificial Intelligence methods often struggle to find global optima due to the “curse of dimensionality”. …”
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EEG analysis of speaking and quiet states during different emotional music stimuli by Xianwei Lin, Xinyue Wu, Zefeng Wang, Zhengting Cai, Zihan Zhang, Guangdong Xie, Lianxin Hu, Laurent Peyrodie

“…In the construction of EEG classification models, the classification performance of deep neural network algorithms is superior to other machine learning algorithms.…”
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The Diagnostic and Predictive Significance of Immune-Related Genes and Immune Characteristics in the Occurrence and Progression of IgA Nephropathy by Jian-Bo Qing, Wen-Zhu Song, Chang-Qun Li, Ya-Feng Li

“…Finally, ssGSEA analysis was performed on the GSE141295 dataset to discover the abnormal inflammation in IgAN. Results. Machine learning (ML) performed excellently in diagnosing IgAN using six DIRGs. …”
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Classification-augmented survival estimation (CASE): A novel method for individualized long-term survival prediction with application to liver transplantation. by Hamed Shourabizadeh, Dionne M Aleman, Louis-Martin Rousseau, Katina Zheng, Mamatha Bhat

“…We improve upon traditional survival machine learning approaches through a novel framework called classification-augmented survival estimation (CASE), which treats survival as a classification task that ultimately yields survival curves, beginning with dataset augmentation to improve class imbalance for use with any classification model. …”
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Federated learning and information sharing between competitors with different training effectiveness by Jiajun Meng, Jing Chen, Dongfang Zhao

“…Federated Learning (FL) is an innovative technique that allows multiple firms to collaborate in training machine learning models while preserving data privacy. …”
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An Improved Deep Learning Model for Traffic Crash Prediction by Chunjiao Dong, Chunfu Shao, Juan Li, Zhihua Xiong

“…Machine-learning technology powers many aspects of modern society. …”
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Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks by Thomas Nowotny, James P Turner, James C Knight

“…Event-based machine learning promises more energy-efficient AI on future neuromorphic hardware. …”
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Secretary bird optimization algorithm based on quantum computing and multiple strategies improvement for KELM diabetes classification by Yu Zhu, Mingxu Zhang, Qinchuan Huang, Xianbo Wu, Li Wan, Ju Huang

“…Given the widespread nature of this chronic condition, numerous researchers are striving to develop robust machine learning algorithms for accurate classification. …”
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Adaptive algorithms for change point detection in financial time series by Alexander Musaev, Dmitry Grigoriev, Maxim Kolosov

“…Key findings reveal that while no universal solution exists for detecting change points in chaotic time series, integrating machine learning and multivariate approaches allows for more robust and adaptive forecasting models. …”
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Electricity theft detection in integrated energy systems considering multi-energy loads by Wenlong Liao, Dechang Yang, Leijiao Ge, Yixiong Jia, Zhe Yang

“…Simulation results demonstrate that the incorporation of heating and cooling loads can significantly enhance the performance of various machine learning models for electricity theft detection. …”
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