Non-destructive estimation of needle leaf chlorophyll and water contents in Chinese fir seedlings based on hyperspectral reflectance spectra by Dong Xing, Penghui Sun, Yulin Wang, Mei Jiang, Siyu Miao, Wei Liu, Huahong Huang, Erpei Lin

“…Moreover, SVM, PLSR and ANNs were utilized to construct models that predict LCC and LWC based on effective wavelengths. …”
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Prognosticating salvage stereotactic radiosurgery outcomes in relapsed primary central nervous system lymphoma: A machine learning-driven decision tree analysis by Huili Zhao, Shenao Zhang, Lang Chen, Xin Liu, Aihong Cao, Peng Du

“…The cohort was randomly divided into training and validation sets (7:3 ratio). The C5.0 algorithm was employed to develop a decision tree model for predicting treatment response. …”
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ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies by Kelly L Hayward, Amy L Johnson, Benjamin J Mckillen, Vikas Bansal, Leigh U Horsfall, Gunter Hartel, Chris Moser, Elizabeth E Powell, Patricia C Valery

“…Accuracy of individual codes and grouped combinations was determined by calculating sensitivity, positive predictive value (PPV), negative predictive value and Cohen’s kappa coefficient (κ).Results The PPVs for ‘grouped cirrhosis’ codes (0.96), hepatocellular carcinoma (0.97) ascites (0.97) and ‘grouped varices’ (0.95) were good (κ all >0.60). …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. …”
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Non-Destructive Early Detection of Drosophila Suzukii Infestation in Sweet Cherries (c.v. <i>Sweet Heart</i>) Based on Innovative Management of Spectrophotometric Multilinear Corre... by Giuseppe Altieri, Mahdi Rashvand Avaei, Attilio Matera, Francesco Genovese, Vincenzo Verrastro, Naouel Admane, Orkhan Mammadov, Sabina Laveglia, Giovanni Carlo Di Renzo

“…To model the data fit/prediction, principal components regression and partial least squares regression algorithms were considered. …”
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Digital Twin-Based Technical Research on Comprehensive Gear Fault Diagnosis and Structural Performance Evaluation by Qiang Zhang, Zhe Wu, Boshuo An, Ruitian Sun, Yanping Cui

“…In terms of technical implementation, combined with HyperMesh 2023 refinement mesh generation, ABAQUS 2023 simulates the stress distribution of gear under thermal fluid solid coupling conditions, the Gaussian process regression (GPR) stress prediction model, and a fault diagnosis algorithm based on wavelet transform and the depth residual shrinkage network (DRSN), and analyzes the vibration signal and stress distribution of gear under normal, broken tooth, wear and pitting fault types. …”
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Quantifying training response in cycling based on cardiovascular drift using machine learning by Artur Barsumyan, Artur Barsumyan, Raman Shyla, Anton Saukkonen, Christian Soost, Jan Adriaan Graw, Rene Burchard, Rene Burchard, Rene Burchard

“…Based on aerobic decoupling (power-to-heart rate ratio) and cardiovascular drift of each test ride, a prediction model was created using ML (Logistic regression, Variational Gaussian Process models and k-nearest neighbors algorithm) that indicated whether or not an athlete was responding to the training. …”
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“Can computed tomographic angiography” solve the puzzle of complexities in the pediatric complex congenital heart disease’s by Javaid Iqbal, Sheikh Riaz Rasool, Tariq Ahmad Gojwari, Naseer Ahmad Choh, Moonisah Rafiq

“…The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for diagnosing CHD were 95.83%, 100%, 100%, 99.35%, and 99.44% for CTA and 76.96%, 99.78%, 98.24%, 96.51%, and 96.69% for TTE respectively. …”
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Artificial Intelligence in Pediatric Blood Transfusion during Anesthesia: A Scoping Review by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, Maryam Aligholizadeh, Siavash Sangi

“…Relevant keywords, including artificial intelligence, machine learning, predictive model, neural network, predictive algorithm, blood transfusion, children, pediatric, neonates, anesthesia, surgery, and operation, were extracted from the Medical Subject Headings (MeSH). …”
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Energy-Environmental Analysis of Retrofitting of a Chilled Water Production System in an Industrial Facility—A Case Study by Tomasz Mróz, Kacper Fórmaniak

“…It achieved a 370 MWh annual primary energy consumption reduction and a 1140 Mg annual carbon dioxide emission reduction. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

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Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning by Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande

“…Most of the current bot detection methods rely on black-box algorithms, raising concerns about their transparency and practical usability. …”
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Blasting Vibration Control Using an Improved Artificial Neural Network in the Ashele Copper Mine by Shida Xu, Tianxiao Chen, Jiaqi Liu, Chenrui Zhang, Zhiyang Chen

“…In this paper, a genetic algorithm (GA) and an artificial neural network (ANN) algorithm were jointly used to construct a neural network model with a 4-5-1 topology to predict the PPV. …”
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Data-Driven Approach for Intelligent Classification of Tunnel Surrounding Rock Using Integrated Fractal and Machine Learning Methods by Junjie Ma, Tianbin Li, Roohollah Shirani Faradonbeh, Mostafa Sharifzadeh, Jianfeng Wang, Yuyang Huang, Chunchi Ma, Feng Peng, Hang Zhang

“…The proposed GBDT-BO model shows promise for predicting surrounding rock quality and guiding dynamic tunnel excavation and support.…”
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Characterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices by Maurizio Morisio, Emanuela Noris, Chiara Pagliarani, Stefano Pavone, Amedeo Moine, José Doumet, Luca Ardito

“…Three supervised binary classification algorithms were used to build models capable of predicting the status of the tree quadrant, using the VIs as predictors. …”
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Machine Learning-Assisted Design of Doping Strategies for High-Voltage LiCoO₂: A Data-Driven Approach by Man Fang, Yutong Yao, Chao Pang, Xiehang Chen, Yutao Wei, Fan Zhou, Xiaokun Zhang, Yong Xiang

“…Specifically, the RF and XGBoost models have the highest fitting performance for IC and EC prediction, with R² values of 0.8882 and 0.8318, respectively. …”
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Integrating fractional-order derivatives of soil and leaf hyperspectral reflectance for improved estimation of mangrove soil organic carbon by Yibo Luo, Chunlin Li, Jinhong Huang, Chengcheng Dong, Junjie Wang

“…This study presents a novel framework integrating fractional-order derivative (FOD) techniques with machine learning algorithms for SOC estimation in mangrove wetlands. …”
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Research on Newton-Krylov Method for Multi-component Flow Heat Transfer Coupled System of High-temperature Gas-cooled Reactor by TANG Huanran, ZHANG Han, LIU Lixun, PENG Xinru, WU Yingjie, GUO Jiong, LI Fu

“…And a matrix-coloring algorithm was used to significantly reduce the number of finite difference times and improve the computational efficiency of DJNK method. …”

Gesture recognition based on flexible solar cells and ultrathin hydrogel film by Rucheng WU, Wenbo DING, Xiaomin XU, Linqi SONG, Weitao XU

“…Daily life involves various gestures, and combining these with smart wearable devices is crucial for improving quality of life.One effective solution to the challenges of gesture recognition and device energy consumption isutilizing the photoelectric conversion characteristics of solar energy-related devices.The data of five commonly used gestures were collected in the research of the combination of flexible solar cells and gesture recognition.Z-Score, low-pass filter, sliding window techniques for signal processing were applied, and successfully achieved 100% predicted accuracy using random forest, support vector machine and neural network algorithms even with small samples which showed that this method had significant advantages in the application of gesture recognition.…”
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Towards Machine Learning Interpretability for Tabular Data with Mixed Data Types by Prativa Pokhrel, Alina Lazar

“…Gradient Boosting (GB) algorithms have been proposed for a variety of automated predictions and classification tasks with applications in many domains. …”
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