Prediction of BRAF and TERT status in PTCs by machine learning-based ultrasound radiomics methods: A multicenter study by Hui Shi, Ke Ding, Xue Ting Yang, Ting Fan Wu, Jia Yi Zheng, Li Fan Wang, Bo Yang Zhou, Li Ping Sun, Yi Feng Zhang, Chong Ke Zhao, Hui Xiong Xu

“…The models underwent training and testing, and comparisons were performed. …”
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The Management of Social Phobia Ýn Residual-Type Schizophrenia with Cognitive Behavioral Therapy by Elif Þimþek Kaygusuz, Filiz Civil Arslan, Gizem Güneþ

“…According to the cognitive model, the impairment of social performance increases the severity of social phobia. …”
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C-parameter version of robust bounded one-class support vector classification by Junyou Ye, Zhixia Yang, Yongxing Hu, Zheng Zhang

“…Nonetheless, the model does not yield a unique decision boundary, and potentially compromises learning performance when the training data is contaminated by some outliers or mislabeled observations. …”
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Improving Weakly-Supervised Video Instance Segmentation by Leveraging Spatio-Temporal Consistency by Farnoosh Arefi, Amir M. Mansourian, Shohreh Kasaei

“…Using the Davies-Bouldin score, the QCC provides an unsupervised measure of feature discrimination, allowing the model to self-evaluate and adapt to varying object distributions, enhancing robustness during the testing phase. …”
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Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER)... by Xu Zheng, Longqiang Shu, Shanyi Lin, Hanqiang Jin, Xiaoyu Wang, Ting Yuan

“…Among 468 patients with high-grade chondrosarcoma, cox proportional hazards models and random survival forests were used for feature selection. …”
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Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output by Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima

“…A core feature of the new model is the self‐estimation structure, wherein the outputs of the physical reservoir are mutually estimated. …”
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SHAP-Instance Weighted and Anchor Explainable AI: Enhancing XGBoost for Financial Fraud Detection by Putthiporn Thanathamathee, Siriporn Sawangarreerak, Siripinyo Chantamunee, Dinna Nina Mohd Nizam

“…This research aims to enhance financial fraud detection by integrating SHAP-Instance Weighting and Anchor Explainable AI with XGBoost, addressing challenges of class imbalance and model interpretability. The study extends SHAP values beyond feature importance to instance weighting, assigning higher weights to more influential instances. …”
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Grape Target Detection Method in Orchard Environment Based on Improved YOLOv7 by Fuchun Sun, Qiurong Lv, Yuechao Bian, Renwei He, Dong Lv, Leina Gao, Haorong Wu, Xiaoxiao Li

“…Firstly, the original backbone network is replaced with MobileOne to achieve a lightweight improvement of the model, thereby reducing the number of parameters. …”
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Multifactorial analysis of factors influencing elite australian football match outcomes: a machine learning approach by Fahey-Gilmour J., Dawson B., Peeling P., Heasman J., Rogalski B.

“…Models that contained in-built feature selection or could model non-linear relationships generally performed better. …”
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Grading chondroid tumors through MRI radiomics: enchondroma, low-grade chondrosarcoma and higher-grade chondrosarcoma by Hyerim Park, Jooyeon Lee, Seungeun Lee, Joon-Yong Jung

“…Model performance was evaluated using five-fold cross-validation with average precision, accuracy, area under the curve (AUC), and weighted kappa statistics. …”
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SPL-YOLOv8: A Lightweight Method for Rape Flower Cluster Detection and Counting Based on YOLOv8n by Yue Fang, Chenbo Yang, Jie Li, Jingmin Tu

“…First, the model introduces StarNet as a lightweight backbone network for efficient feature extraction, significantly reducing computational complexity and parameter counts. …”
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Digital Biomarkers for Diagnosis of Muscle Disorders Using Stimulated Muscle Contraction Signal by Kwangsub Song, Sangui Choi, Jin-Hong Shin, Woo-Hyeon Son, Hyuntae Park, Hooman Lee, Nam-Jong Paik

“…Finally, to estimate the strength and endurance of the muscle, the feature vector was passed through the DB estimation model learned through the MLP. …”
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RUL Prediction for Lithium Battery Systems in Fuel Cell Ships Based on Adaptive Modal Enhancement Networks by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Jiaxin Luo, Lei Han, Junting Lang, Weixin Zhao

“…This results in a comprehensive prediction framework that spans signal decomposition, feature enhancement, and time-series modeling. The method is validated on several public datasets, and the results demonstrate that each component of the RIME-VMD-SEInformer framework is both necessary and justifiable, leading to improved performance. …”
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An Efficient Printing Defect Detection Based on YOLOv5-DCN-LSK by Jie Liu, Zelong Cai, Kuanfang He, Chengqiang Huang, Xianxin Lin, Zhenyong Liu, Zhicong Li, Minsheng Chen

“…To overcome this problem, we propose an improved model based on the structure of the YOLOv5 network to enhance the detection performance of printing defects. …”
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Production Capacity Prediction for Tight Gas Reservoirs Based on ADASVRLGBM by MENG Sihai, ZHANG Zhansong, GUO Jianhong, HAN Zihao, ZENG Weijie, LYU Hengyang

“…The integrated model systematically analyzes the correlation of factors influencing tight gas production, extracts key feature parameters, and builds a predictive model with gas well production capacity as the output label. …”
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Air quality prediction using stacked bi- long short-term memory and convolutional neural network in India by S Karkuzhali, Thendral Puyalnithi, R Nirmalan

“…Through meticulous preprocessing - encompassing missing value handling, normalization, and temporal sequencing - the dataset is prepared for the Stacked Bi-LSTM and CNN hybrid model. The model architecture leverages the temporal sequence-capturing capabilities of Stacked Bi-LSTM layers, enhancing it with the spatial feature extraction prowess of CNN layers. …”
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Reconstruction of Sea Surface Chlorophyll-a Concentration in the Bohai and Yellow Seas Using LSTM Neural Network by Qing Xu, Guiying Yang, Xiaobin Yin, Tong Sun

“…Performance inter-comparisons between LSTM and other machine learning or deep learning models was conducted based on OC-CCI (Ocean Color Climate Change Initiative) Chl-a product. …”
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Debris Flow Susceptibility Prediction Using Transfer Learning: A Case Study in Western Sichuan, China by Tiezhu Li, Qidi Huang, Qigang Chen

“…Model performance was rigorously evaluated through ten-fold cross-validation, and hyperparameter optimization was employed to enhance predictive accuracy. …”
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Realtime Multispectral Pedestrian Detection With Visible and Far-Infrared Under Ambient Temperature Changing by Masato Okuda, Kota Yoshida, Takeshi Fujino

“…To further improve detection performance, we built a new model called YOLOv8s-2stream. …”
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A Distributed Privacy Preserved Federated Learning Approach for Revolutionizing Pneumonia Detection in Isolated Heterogenous Data Silos by Shagun Sharma, Kalpna Guleria

“…Centralized deep learning enhances the feature extraction process and optimally improves the prediction outcomes; however, these models have data privacy concerns due to centralized storage systems. …”
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