Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy by Wei Hua, Jie Liu, Yue Li, Hua Yin, Hao‐Rui Shen, Jia‐Zhu Wu, Yi‐Lin Kong, Bi‐Hui Pan, Jun‐Heng Liang, Li Wang, Jian‐Yong Li, Rui Gao, Jin‐Hua Liang, Wei Xu

“…By employing various machine learning algorithms, we pinpointed eight pivotal genes linked to PCD, specifically FLT3, SORL1, CD8A, BCL2L1, COL13A1, MPG, DYRK2 and CAMK2B. …”
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Development and validation of a machine learning model to predict the risk of lymph node metastasis in early-stage supraglottic laryngeal cancer by Hongyu Wang, Hongyu Wang, Hongyu Wang, Zhiqiang He, Zhiqiang He, Zhiqiang He, Jiayang Xu, Jiayang Xu, Ting Chen, Ting Chen, Ting Chen, Jingtian Huang, Jingtian Huang, Jingtian Huang, Lihong Chen, Lihong Chen, Lihong Chen, Xin Yue, Xin Yue, Xin Yue

“…This study seeks to create and validate a predictive model through the application of machine learning (ML) algorithms.MethodsThe training set and internal validation set data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. …”
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Quantifying the Robustness of Countries’ Competitiveness by Network-Based Methods by Ming-Yang Zhou, Xiao-Yu Li, Wen-Man Xiong, Hao Liao

“…In this paper, we use perturbation to quantify the robustness of countries using two renowned algorithms: method of reflections (MR) and fitness-complexity method (FCM). …”
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Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) by Ani Apriani, Nono Carsono, Mas Dadang Enjat Munajat

“…Keywords: Prediction, Algorithm, SVM. Linear Regression.…”
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A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy by Yaoying Wang

“…Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. …”
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Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model by Changming Liu, Di Zhou, Zhigang Wang, Dan Yang, Gangbing Song

“…Acoustic emission (AE) technique is a common approach to identify the damage of the refractories; however, there is a complex problem since there are as many as fifteen involved parameters, which calls for effective data processing and classification algorithms to reduce the level of complexity. In this paper, experiments involving three-point bending tests of refractories were conducted and AE signals were collected. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

“…We demonstrate how existing open-source datasets can be spatially integrated and subsequently used as training for machine learning (ML) models to predict building occupancy type, a major component needed for disaster preparedness and decision -making. Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. …”
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Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer by Lianbo Ma, Kunyuan Hu, Yunlong Zhu, Ben Niu, Hanning Chen, Maowei He

“…The experimental results demonstrate remarkable performance of the HABC algorithm when compared with other six evolutionary algorithms.…”
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Angular and CP-Violation Analyses of B-→D⁎+l-ν-l Decays at Hadron Collider Experiments by Daniele Marangotto

“…This article proposes the measurement of B-→D⁎+l-ν-l angular and CP-violating observables at hadron collider experiments, by exploiting approximate reconstruction algorithms using information from detectable final-state particles only. …”
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Prediction of Later-Age Concrete Compressive Strength Using Feedforward Neural Network by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…In this investigation, an approach using a feedforward neural network (FNN) machine learning algorithm was proposed to predict the compressive strength of later-age concrete. …”
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Chaotic Image Encryption Based on Running-Key Related to Plaintext by Cao Guanghui, Hu Kai, Zhang Yizhi, Zhou Jun, Zhang Xing

“…In the field of chaotic image encryption, the algorithm based on correlating key with plaintext has become a new developing direction. …”
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Empowering drones in vehicular network through fog computing and blockchain technology. by Shivani Wadhwa, Divya Gupta, Shalli Rani, Maha Driss, Wadii Boulila

“…Furthermore, the model evaluates blockchain consensus algorithms (PoW, PoS, DAG) and recommends DAG for superior performance in handling IoT data. …”
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A Computational Complexity-Based Method for Predicting Scholars’ Ages through Articles’ Information by Jun Zhang, Xiaoyan Su, Mingliang Hou, Jing Ren

“…Our method first classifies factors that affect scholars’ ages into intuitive and complex types according to their computational complexity and then apply machine learning algorithms to predict the ages of scholars based on these factors. …”
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Growth Rates of  Morphometric Variables in Approximately Linear Sections Using Lines in R3 by Aquiles E. Darghan, Enrique Quevedo García, Sergio Esteban Gamboa Muñoz, Carlos Armando Rivera Moreno

“…In this research, different classification algorithms are applied to select the approximately linear phase present in various nonlinear models of variables or parameters used in the modeling of the growth of a crop. …”
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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
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Accurate Nodes Localization in Anisotropic Wireless Sensor Networks by Ahmad El Assaf, Slim Zaidi, Sofiène Affes, Nahi Kandil

“…An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSNs) is proposed in this paper. …”
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Relation Between Quantum Advantage in Supervised Learning and Quantum Computational Advantage by Jordi Perez-Guijarro, Alba Pages-Zamora, Javier R. Fonollosa

“…In both cases, the existence of efficient algorithms to generate training sets emerges as the cornerstone of such conditions, although, for the distribution-independent definition, additional mild conditions must also be met. …”
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On Oscillations and Noise in Multicomponent Adsorption: The Nature of Multiple Stationary States by Olga M. Jakšić, Zoran Jakšić, Milena B. Rašljić, Ljiljana Z. Kolar-Anić

“…We address perturbations around the steady state analytically, first in a classical way, then by introducing Langevin forces and analyzing the reaction flux and cross-correlations, then by applying the stochastic chemical master equation approach, and finally, numerically, by using stochastic simulation algorithms. Our results show that stationary states in this model are stable nodes. …”
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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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Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model by Weiying Wang, Zhiqiang Xu, Rui Tang, Shuying Li, Wei Wu

“…Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.…”
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