Pioneering machine learning techniques to estimate thermal conductivity of carbon-based phase change materials: A comprehensive modeling framework by Raouf Hassan, Alireza Baghban

“…Among them, CatBoost achieved the highest predictive performance with an R2 of 0.979 and the lowest mean squared error (MSE) of 0.006 on the test set. SHAP analysis revealed that nanoparticle concentration was the most influential feature. …”
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Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network by Fatemeh Makhloughi

“…Initially, each color channel is treated as a time series input to a 1DCNN model, facilitating bilirubin level prediction through regression analysis. Subsequently, RGB feature maps are combined with those derived from HSV, LAB, and YCbCr channels to enhance prediction performance. …”
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Advances in automated tongue diagnosis techniques by Marzia Hoque Tania, Khin Lwin, Mohammed Alamgir Hossain

“…This work reviews the recent advances in tongue diagnosis, which is a significant constituent of traditional oriental medicinal technology, and explores the literature to evaluate the works done on the various aspects of computerized tongue diagnosis, namely preprocessing, tongue detection, segmentation, feature extraction, tongue analysis, especially in traditional Chinese medicine (TCM). …”
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A Short-Term Risk Prediction Method Based on In-Vehicle Perception Data by Xinpeng Yao, Nengchao Lyu, Mengfei Liu

“…The method incorporates Monte Carlo simulation for threshold calibration, Boruta-based feature selection, and multiple machine learning models, including the light gradient-boosting machine (LGBM), with performance interpretation via SHAP analysis. …”
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From Image to Sequence: Exploring Vision Transformers for Optical Coherence Tomography Classification by Amirali Arbab, Aref Habibi, Hossein Rabbani, Mahnoosh Tajmirriahi

“…The synergy between CNNs, which excel at extracting detailed localized features, and ViT, adept at recognizing long-range patterns, enables a more effective and comprehensive analysis of OCT images. …”
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Development Process and Characteristics Study of Tree Line Discharge in 10 kV Overhead Power Lines by XU Huikai, HUANG Xiaolong, YANG Chunlan, CHEN Tianxiang, YANG Nongchao, CHEN Long

“…These features can be manifested in electrical signals, as well as in ultrasonic and ground waves. …”
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Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines by Eren Erdogan, Michael Schmidt, Andreas Goss, Barbara Görres, Florian Seitz

“…Abstract Monitoring the Vertical Total Electron Content (VTEC) of the ionosphere is important for applications ranging from navigation to detection of space weather events. Therefore, emerging efforts have been made by several analysis centers to estimate the VTEC using different approaches in real‐time. …”
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Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals’ Electroencephalography Signals by Illia Pidvalnyi, Anna Kostenko, Oleksandr Sudakov, Dmytro Isaev, Oleksandr Maximyuk, Oleg Krishtal, Olena Iegorova, Ievgen Kabin, Zoya Dyka, Steffen Ortmann, Peter Langendorfer

“…A principal component analysis was applied for feature selection before using a support vector machine for the detection of seizures. …”
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A Handheld IoT Vis/NIR Spectroscopic System to Assess the Soluble Solids Content of Wine Grapes by Xu Zhang, Ziquan Qin, Ruijie Zhao, Zhuojun Xie, Xuebing Bai

“…After simultaneously removing outliers detected by both Monte Carlo (MC) and principal component analysis (PCA) methods from the raw spectra, the SSC prediction model was established, resulting in an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi>V</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula> of 0.697. …”
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Machine learning-based prediction of respiratory depression during sedation for liposuction by Jin-Woo Kim, Jae Hee Woo, Jaewon Seo, Hajin Kim, Sunho Lee, Younchan Park, Jaehyun Ahn, Seonghun Hong, Hye-Min Jeong, Yuncheol Kang

“…SHAP analysis, an explainable AI approach, was conducted to visually interpret feature importance. …”
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Battery state of health estimation under fast charging via deep transfer learning by Jingyuan Zhao, Di Li, Yuqi Li, Dapai Shi, Jinrui Nan, Andrew F. Burke

“…With approximately 22,000 parameters, the model effectively estimates battery capacity by combining local feature extraction (convolutional neural networks [CNNs]) and global dependency analysis (self-attention). …”
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Spatio-temporal Variation of Ecological Service Values in Lijiang River Basin During 2000—2020 by Zhang Junmin, Rong Cheng, Dong Guosong

“…[Methods] Based on remote sensing information mining and a geographic information analysis platform, ecological service values were evaluated by value accounting and its dynamic and sensitivity analysis methods. …”
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Using Partial Differential Equation Face Recognition Model to Evaluate Students’ Attention in a College Chinese Classroom by Xia Miao, Ziyao Yu, Ming Liu

“…The extracted features are invariant to rotation and translation and more robust to illumination changes. …”
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Quantitative determination of the spatial distribution of components in single cells with CellDetail by Tanja Schuster, Amanda Amoah, Angelika Vollmer, Gina Marka, Julian Niemann, Mehmet Saçma, Vadim Sakk, Karin Soller, Mona Vogel, Ani Grigoryan, Meinhard Wlaschek, Karin Scharffetter-Kochanek, Medhanie Mulaw, Hartmut Geiger

“…To quantitatively determine the spatial distribution of components inside cells, we built the user-friendly open-source 3D-cell-image analysis platform Cell Detection and Analysis of Intensity Lounge (CellDetail). …”
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Quantitative Prediction of Protein Content in Corn Kernel Based on Near-Infrared Spectroscopy by Chenlong Fan, Ying Liu, Tao Cui, Mengmeng Qiao, Yang Yu, Weijun Xie, Yuping Huang

“…Rapid and accurate detection of protein content is essential for ensuring the quality of maize. …”
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A Novel Foundation Model-Based Framework for Multimodal Retinal Age Prediction by Christopher Nielsen, Matthias Wilms, Nils D. Forkert

“…Technology or Method: Feature representations from CFP and OCT images were extracted using RETFound, a powerful foundation model for retinal image analysis. …”
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Machine learning for predicting metabolic-associated fatty liver disease including NHHR: a cross-sectional NHANES study. by Liyu Lin, Yirui Xie, Zhuangteng Lin, Cuiyan Lin, Yichun Yang

“…Furthermore, NHHR was identified as the second most important feature in the SHAP analysis, following body mass index (BMI), highlighting its potential in predicting MAFLD.…”
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Determination of brown egg fertility by multi-directional visible/near-infrared spectroscopy and machine learning by Seyyedeh Arefeh Hosseini, Ahmad Banakar, Saeid Minaei, Saman Abdanan Mehdizadeh, Mohamad Amir Karimi Torshizi, Guoming Li

“…Four preprocessing methods (e.g., Savitzky-Golay, Gaussian, Multiplicative Scatter Correction, and Standard Normal Variet) were separately or jointly applied to filter un-wanted data and noises in spectrums. Then feature selection was performed using Principal Component Analysis and T-test. …”
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A multi-biomarker machine learning approach for early prediction of interstitial lung disease in rheumatoid arthritis by Jiaojiao Xu, Wei Zhang, Weili Bai, Nannan Gai, Jing Li, Yunqi Bao

“…Results The XGBoost model demonstrated superior predictive performance (AUC = 0.891, 95% CI: 0.847–0.935). Feature importance analysis identified Krebs von den Lungen-6 (KL-6) as the strongest predictor (importance score = 0.285), followed by interleukin-6 (IL-6) and cytokeratin 19 fragment (CYFRA21-1). …”
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Bearing Early Fault Diagnosis Based on an Improved Multiscale Permutation Entropy and SVM by Qunyan Jiang, Juying Dai, Faming Shao, Shengli Song, Fanjie Meng

“…In the early stage of the fault, if it can be found out in time and taken reasonable prevention and elimination measures, we can avoid serious losses and safety accidents. Therefore, the feature extraction and analysis of early weak fault has important practical significance. …”
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