Abstract 045: A Radiomics Based Pipeline for Paired Risk‐Stratification of Intracranial Atherosclerotic Plaques by Elena S. Sagues Sese, Sebastian Sanchez, Sricharan Veeturi, Tatsat Patel, Vicent M. Tutino, Diego J. Ojeda, Jacob M. Miller, Arshaq Saleem, Andres Gudino, Bincheng Wang, Edgar A. Samaniego

“…Three‐dimensional segmentation of the plaque was performed, and RFs were extracted. We then evaluated multiple machine learning models to predict and identify culprit plaques using significantly different RFs. …”
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AI-augmented differential diagnosis of granulomatous rosacea and lupus miliaris disseminatus faciei: A 23-year retrospective pilot study. by Sang-Hoon Lee, Hyun Kang, Seung-Phil Hong, Eung Ho Choi, Joong Lee, Minseob Eom

“…This study evaluates artificial intelligence (AI)-based models for differentiating between GR and LMDF and assess their impact on clinician performance. …”
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Quantitative bias analysis for mismeasured variables in health research: a review of software tools by Codie J. C. Wood, Kate Tilling, Jonathan W. Bartlett, Rachael A. Hughes

“…However, there is a lack of software tools performing QBA for misclassification of categorical variables and measurement error outside of the classical model. …”
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Multisensor Remote Sensing and AI-Driven Analysis for Coastal and Urban Resilience Classification by Sumei Ren, Bushra Ghaffar, Muhammad Mubbin, Muhammad Haseeb, Zainab Tahir, Sher Shah Hassan, Dmitry E. Kucher, Olga D. Kucher, M. Abdullah-Al-Wadud

“…The proposed LSTM model is optimized to enhance performance with dropout regularization (0.3), an Adam optimizer (learning rate = 0.0003), and class weighting strategies. …”
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Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Tra... by Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

“…Before building the CNN model, NL-SGS-D₂ was utilized to enhance the feature extraction capability of model by eliminating the background noise. …”
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Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma by Shuang Qu, Zhihai Zheng, Xiaoling Guo, Jiaqi Mei, Sicong Jiang, Biyun Chen

“…Ultimately, an investigation was conducted into the association between the risk model and various immunological features, in terms of antitumor immunotherapy, the tumor microenvironment, and immune checkpoints. …”
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BoneCLIP-XGBoost: A Multimodal Approach for Bone Fracture Diagnosis by Zhihao Su, Yuhuai Zhou, Jianqun Zhou, Hanhua Cao, Huanping Zhang

“…Our ablation study highlights the model’s exceptional performance, demonstrating an accuracy of 88.5%, precision of 87.3%, recall of 86.8%, and an F1 score of 87.0% when both image and text data are utilized. …”
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YOLO-BS: a traffic sign detection algorithm based on YOLOv8 by Hong Zhang, Mingyin Liang, Yufeng Wang

“…A small object detection layer was incorporated into the YOLOv8 framework to enrich feature extraction. Additionally, a bidirectional feature pyramid network (BiFPN) was integrated into the detection framework to enhance the handling of multi-scale objects and improve the performance in detecting small objects. …”
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Implementation of Random Forest Method with Information Gain Selection and Hyperparameter Tuning for Alzheimer’s Disease Classification by Riska Nuril Fadhila, Nurissaidah Ulinnuha, Dian Yuliati, Nurissaidah Ulinnuha, Dian Yuliati

“…Random Forest with Information Gain and Grid Search gave an accuracy of 95.57%, sensitivity of 92.93%, and specificity of 96.99%, which showed better performance than the Random Search method. This indicates that parameter optimization has a vital role in improving model performance. …”
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Mitigating Bias Due to Race and Gender in Machine Learning Predictions of Traffic Stop Outcomes by Kevin Saville, Derek Berger, Jacob Levman

“…We also observed correlations between model performance and both race and gender. While these findings imply the existence of discrimination based on race and gender, our large-scale analysis (>600,000 samples) demonstrates the ability to produce top performing models that are gender and race agnostic, implying the potential to create technology that can help mitigate bias in traffic stops. …”
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A Novel Real-Time Battery State Estimation Using Data-Driven Prognostics and Health Management by Juliano Pimentel, Alistair A. McEwan, Hong Qing Yu

“…The method leverages an optimized bidirectional Long Short-Term Memory (Bi-LSTM) network, trained with enhanced datasets filtered via exponentially weighted moving averages (EWMAs) and refined through SHAP-based feature attribution. Compared against a Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) across ten diverse drive cycles, the proposed model consistently achieved superior performance, with mean absolute errors (MAEs) as low as 0.40%, outperforming EKF (0.66%) and UKF (1.36%). …”
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Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology by C. Jayasri, V. Balaji, C. M. Nalayini, S. Pradeep

“…Experimental results demonstrate that the proposed ILSTM-COA model significantly outperforms existing techniques, achieving 98.9% accuracy and showing notable improvements across sensitivity, specificity, and other performance metrics. …”
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The Detection and Classification of Scaphoid Fractures in Radiograph by Using a Convolutional Neural Network by Tai-Hua Yang, Yung-Nien Sun, Rong-Shiang Li, Ming-Huwi Horng

“…Results: The proposed model performs well in both scaphoid bone detection and fracture classification. …”
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Cascade Learning Early Classification: A Novel Cascade Learning Classification Framework for Early-Season Crop Classification by Weilang Kong, Xiaoqi Huang, Jialin Liu, Min Liu, Luo Liu, Yubin Guo

“…Existing methods mainly focus on enhancing the model’s ability to extract features from limited data to address this challenge, but the extracted critical phenological information remains insufficient. …”
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Imitating Human Go Players via Vision Transformer by Yu-Heng Hsieh, Chen-Chun Kao, Shyan-Ming Yuan

“…Using a dataset from the KGS Go server, our ViT-based model achieves 51.49% accuracy in predicting expert moves with a simple feature set. …”
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Predicting sport event outcomes using deep learning by Jianxiong Gao, Yi Cheng, Jianwei Gao

“…The 1D CNN effectively captures local spatial patterns in structured match data, while the Transformer leverages self-attention mechanisms to model long-range dependencies. This hybrid design enables the model to uncover nuanced feature interactions critical to outcome prediction. …”
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LMVT: A hybrid vision transformer with attention mechanisms for efficient and explainable lung cancer diagnosis by Jesika Debnath, Al Shahriar Uddin Khondakar Pranta, Amira Hossain, Anamul Sakib, Hamdadur Rahman, Rezaul Haque, Md.Redwan Ahmed, Ahmed Wasif Reza, S M Masfequier.Rahman Swapno, Abhishek Appaji

“…Statistical significance tests and confidence intervals confirm the reliability of these performance metrics, while an analysis of model complexity supports its capability for potential deployment. …”
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Application of support vector machine system introducing multiple submodels in data mining by Weinan Tang

“…By introducing open-source tools such as OpenCV, image feature extraction can be performed on large-scale video data. …”
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Fault Detection and Diagnosis in Air-Handling Unit (AHU) Using Improved Hybrid 1D Convolutional Neural Network by Prince, Byungun Yoon, Prashant Kumar

“…While conventional convolutional neural networks (CNNs) effectively detect defects, incorporating more spatial variables could enhance their performance further. This paper presents a hybrid architecture combining a CNN model with a long short-term memory (LSTM) model to diagnose the faults in AHUs. …”
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Multi-Label Classification for Opinion Mining in The Presidential Election using TF-IDF with NB And SVM by Ricy Ardiansyah, Herman Yuliansyah, Anton Yudhana

“…The model combines Naïve Bayes (NB) and Support Vector Machine (SVM) for opinion mining using public data and TF-IDF for feature extraction, applying Multinomial and Linear kernels. …”
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