GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force by Chandrasen Pandey, Diptendu Sinha Roy, Ramesh Chandra Poonia, Ayman Altameem, Soumya Ranjan Nayak, Amit Verma, Abdul Khader Jilani Saudagar

“…The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force. …”
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Extreme Gradient Boosting Model with SMOTE for Heart Disease Classification by Ahmad Ubai Dullah, Aditya Yoga Darmawan, Dwika Ananda Agustina Pertiwi, Jumanto Unjung

“…Along with the development of technology, various models of machine learning algorithms and data processing techniques have been developed to find models that can produce the best precision in classifying heart disease. machine learning algorithm model in classifying heart disease, so that it can improve the effectiveness of diagnosis and help in determining the right treatment for patients. …”
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Protocol to generate dual-target compounds using a transformer chemical language model by Sanjana Srinivasan, Jürgen Bajorath

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Algorithmic Generation of Parameterized Geometric Models of the Aortic Valve and Left Ventricle by Nikita Pil, Alex G. Kuchumov

“…As fluid–structure interaction simulations are highly computationally demanding, machine-learning techniques can be considered a good alternative. …”
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Klasifikasi Aktivitas Manusia Menggunakan Metode Long Short-Term Memory by Latansa Nurry Izza Afida, Fitra Abdurrachman Bachtiar, Imam Cholissodin

“…Selain tingginya dimensi, pada penelitian sebelumnya, banyaknya jumlah label dengan menerapkan machine learning tradisional tidak mampu melebihi akurasi 88%. …”
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Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process by Vitaliy Pozdnyakov, Aleksandr Kovalenko, Ilya Makarov, Mikhail Drobyshevskiy, Kirill Lukyanov

“…Integrating machine learning into Automated Control Systems (ACS) enhances decision-making in industrial process management. …”
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Is There a Difference in the Perception of City in Pre-Pandemic and Peri-Pandemic on Social Media? Case Study from Taiwan by Yulin Chen

“…The purpose of this study was to consolidate machine learning applications and develop a method to simultaneously analyze unstructured text and images pertaining to travel and tourism. …”
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Flight Delay Classification Prediction Based on Stacking Algorithm by Jia Yi, Honghai Zhang, Hao Liu, Gang Zhong, Guiyi Li

“…There are five supervised machine learning algorithms in the first-level learner of Stacking including KNN, Random Forest, Logistic Regression, Decision Tree, and Gaussian Naive Bayes. …”
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A CNN-Based Microwave Imaging System for Detecting Watermelon Ripeness by Zachary M. Choffin, Lingyan Kong, Yu Gan, Nathan Jeong

“…The integration of a non-invasive microwave imaging system with a machine learning algorithm could improve food quality and food safety. …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…We performed hyperparameter tuning with grid search CV on Machine Learning algorithms such as Ada Boost and Gradient Boosting. …”
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The Construction of Corporate Financial Management Risk Model Based on XGBoost Algorithm by Rongyuan Qin

“…With the continuous development of intelligent algorithms and machine learning algorithms, new ideas have been brought to enterprise financial risk assessment. …”
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A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution. by Sheng Miao, Guoqing Ni, Guangze Kong, Xiuhe Yuan, Chao Liu, Xiang Shen, Weijun Gao

“…The results indicate that compared with traditional Kriging3D methods (R2 = 0.318) and other machine learning methods such as support vector regression (R2 = 0.582), the proposed 3DCNN based method can achieve better accuracy (R2 = 0.954). …”
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Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections by Nayana Damiani Macedo, Aline Rodrigues Buzin, Isabela Bastos de Araujo, Breno Valentim Nogueira, Tadeu Uggere Andrade, Denise Coutinho Endringer, Dominik Lenz

“…Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells. …”
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Application of Particle Transformer to quark flavor tagging in the ILC project by Tagami Risako, Suehara Taikan, Ishino Masaya

“…Particle Transformer (ParT) is a machine learning model based on Transformer architecture developed for jet analysis, including jet flavor tagging. …”
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Application of an improved LightGBM hybrid integration model combining gradient harmonization and Jacobian regularization for breast cancer diagnosis by Xiaoyan Sun

“…In recent years, intelligent medical assistants supported by data mining and machine learning algorithms have provided necessary support for doctors’ diagnosis. …”
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Survey on vertical federated learning: algorithm, privacy and security by Jinyin CHEN, Rongchang LI, Guohan HUANG, Tao LIU, Haibin ZHENG, Yao CHENG

“…Federated learning （FL） is a distributed machine learning technology that enables joint construction of machine learning models by transmitting intermediate results （e.g., model parameters, parameter gradients, embedding representation, etc.） applied to data distributed across various institutions.FL reduces the risk of privacy leakage, since raw data is not allowed to leave the institution.According to the difference in data distribution between institutions, FL is usually divided into horizontal federated learning （HFL）, vertical federated learning （VFL）, and federal transfer learning （TFL）.VFL is suitable for scenarios where institutions have the same sample space but different feature spaces and is widely used in fields such as medical diagnosis, financial and security of VFL.Although VFL performs well in real-world applications, it still faces many privacy and security challenges.To the best of our knowledge, no comprehensive survey has been conducted on privacy and security methods.The existing VFL was analyzed from four perspectives: the basic framework, communication mechanism, alignment mechanism, and label processing mechanism.Then the privacy and security risks faced by VFL and the related defense methods were introduced and analyzed.Additionally, the common data sets and indicators suitable for VFL and platform framework were presented.Considering the existing challenges and problems, the future direction and development trend of VFL were outlined, to provide a reference for the theoretical research of building an efficient, robust and safe VFL.…”
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Application of Internet of Things Based on Big Data Ecosystem in Factory Energy Consumption Analysis Model by Ang Li, Chen Zhang, Lei Li

“…In 2019, the average ratio of decision tree algorithm, machine learning algorithm, and machine learning algorithm was 36.8%, 37.4%, and 43.5%, respectively. …”
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Unleashing the Power of Artificial Intelligence-Driven Drug Discovery in Streptomyces by Wei-Shan Ang, Jodi Woan-Fei Law, Yatinesh Kumari, Vengadesh Letchumanan, Loh Teng-Hern Tan

“…Graphical abstract: The role of machine learning in drug discovery from Streptomyces. …”
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A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes by Ali H. Ibrahem, Adnan M. Abdulazeez

“… Beauty multi-task prediction from facial attributes is a multidisciplinary challenge at the intersection of computer vision, machine learning, and psychology. Despite the centrality of beauty in human perception, its subjective nature—shaped by individual, social, and cultural influences—complicates its computational modeling. …”
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Framework for Holistic Online Optimization of Milling Machine Conditions to Enhance Machine Efficiency and Sustainability by Alexander Bott, Simon Anderlik, Robin Ströbel, Jürgen Fleischer, Andreas Wortmann

“…The research method involved the development of the framework for the realisation and analysis of measurement data from milling machines, focusing on six machine parts and employing a machine learning system for optimization and evaluation. …”
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