Development and validation of a deep learning-based pathomics signature for prognosis and chemotherapy benefits in colorectal cancer: a retrospective multicenter cohort study by Shenghan Lou, Yanming Huang, Fenqi Du, Jingmin Xue, Genshen Mo, Hao Li, Zhanjiang Yu, Yuanchun Li, Hang Wang, Yuze Huang, Haonan Xie, Wenjie Song, Xinyue Zhang, Huiying Li, Chun Lou, Peng Han, Peng Han, Peng Han

“…An interpretable multi-instance learning model was developed to construct PSCRC, with SHapley Additive exPlanations (SHAP) and gradient-weighted class activation mapping (Grad-CAM) for the improvement of model interpretability and the identification of critical histopathological features, respectively. …”
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Multimodal consumer choice prediction using EEG signals and eye tracking by Syed Muhammad Usman, Shehzad Khalid, Aimen Tanveer, Ali Shariq Imran, Muhammad Zubair

“…Electroencephalogram (EEG) has typically been utilized by researchers for neuromarketing, whereas Eye Tracking (ET) has remained unexplored. To address this gap, we propose a novel multimodal approach to predict consumer choices by integrating EEG and ET data. …”
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An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures by Andrzej D. Dobrzycki, Ana M. Bernardos, José R. Casar

“…We systematically investigate multiple freezing configurations across YOLOv8 and YOLOv10 variants using four challenging datasets that represent critical infrastructure monitoring. Our methodology integrates a gradient behavior analysis (L2 norm) and visual explanations (Grad-CAM) to provide deeper insights into training dynamics under different freezing strategies. …”
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Engaging biological oscillators through second messenger pathways permits emergence of a robust gastric slow-wave during peristalsis. by Md Ashfaq Ahmed, Sharmila Venugopal, Ranu Jung

“…Understanding of the integrative role of neurotransmission and intercellular coupling in the propagation of an entrained gastric slow-wave, important for understanding motility disorders, however, remains incomplete. …”
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Advanced hybrid machine learning models with explainable AI for predicting residual friction angle in clay soils by Mawuko Luke Yaw Ankah, Shalom Adjei-Yeboah, Yao Yevenyo Ziggah, Edmund Nana Asare

“…This study explores three advanced hybrid machine learning models: Gradient Boosting Neural Network (GrowNet), Reinforcement Learning Gradient Boosting Machine (RL-GBM), and a Stacking Ensemble to predict the residual friction angle of clay soils, addressing a critical gap in current predictive methodologies. …”
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Multi-Agent Deep Reinforcement Learning Cooperative Control Model for Autonomous Vehicle Merging into Platoon in Highway by Jiajia Chen, Bingqing Zhu, Mengyu Zhang, Xiang Ling, Xiaobo Ruan, Yifan Deng, Ning Guo

“…To enhance training efficiency, we develop a dual-layer multi-agent maximum Q-value proximal policy optimization (MAMQPPO) method, which extends the multi-agent PPO algorithm (a policy gradient method ensuring stable policy updates) by incorporating maximum Q-value action selection for platoon gap control and discrete command generation. …”
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Leveraging LIME for Trustworthy Apple Quality Assessment by İsmail Kırbaş, Ahmet Çifci

“…This study explores the integration of machine learning (ML) models and explainable artificial ıntelligence (XAI) techniques to enhance the accuracy and transparency of apple quality assessment. …”
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How Long Until Agricultural Carbon Peaks in the Three Gorges Reservoir? Insights from 18 Districts and Counties by Danqing Li, Yunqi Wang, Huifang Liu, Cheng Li, Jinhua Cheng, Xiaoming Zhang, Peng Li, Lintao Wang, Renfang Chang

“…Pathway scenario prediction: We construct three developmental scenarios (low-carbon transition, business-as-usual, and high-resource dependency) integrated with regional planning parameters. This framework enables the identification of optimal peaking chronologies for each county and proposes gradient peaking strategies through spatial zoning, thereby resolving fragmented carbon governance in agrarian counties. …”
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SOC Estimation of Lithium-Ion Batteries Utilizing EIS Technology with SHAP–ASO–LightGBM by Panpan Hu, Chun Yin Li, Chi Chung Lee

“…This paper proposes a novel machine learning-based approach for SOC estimation by integrating Electrochemical Impedance Spectroscopy (EIS) with the SHapley Additive exPlanations (SHAP) method, Atom Search Optimization (ASO), and Light Gradient Boosting Machine (LightGBM). …”
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Numerical modeling and analysis of plasmonic flying head for rotary near-field lithography technology by Yueqiang Hu, Yonggang Meng

“…The linewidth has a strong correlation with the near-field gap, and the manufacturing uniformity is directly influenced by the dynamic performance. …”
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A machine learning based estimation method of beach slopes at a national scale: a case study of New Zealand by Hao Xu, Nan Xu, Chi Zhang, Shanhang Chi, Yuan Li, Wenyu Li, Yifu Ou, Jiaqi Yao, Han-Su Zhang, Fan Mo, Hui Lu

“…We developed robust coastal slope estimation models for sandy beaches by integrating 12 environmental factors with high-precision LiDAR-derived slope data, employing four machine learning regression techniques: Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost), and Category Boosting (CatBoost). …”
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Natural barriers facing female cyclists and how to overcome them: A cross national examination of bikesharing schemes by Richard Bean, Dorina Pojani, Jonathan Corcoran

“…For the analysis, we spatially integrate gender for more than 200 million bikesharing trips with fine-grained weather, gradient, and sunset/sunrise data. …”
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XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…Future research directions include prospective validation across diverse populations, integration of longitudinal data, and further exploration of explainable AI techniques to bridge the gap between algorithmic predictions and clinical implementation.…”
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Altitudinal Variations in Coniferous Vegetation and Soil Carbon Storage in Kalam Temperate Forest, Pakistan by Bilal Muhammad, Umer Hayat, Lakshmi Gopakumar, Shuangjiang Xiong, Jamshid Ali, Muhammad Tariq Badshah, Saif Ullah, Arif UR Rehman, Qun Yin, Zhongkui Jia

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Linear and Tree‐Based Intelligent Investigation of Cross‐Domain Housing Features to Enhance Energy Efficiency by Hafiz Muhammad Shakeel, Shamaila Iram, Hafiz Muhammad Athar Farid, Richard Hill

“…These approaches overlook the potential insights gained from integrating data across different domains. This research addresses this gap using a cross‐domain dataset that includes building characteristics, energy usage, and environmental factors. …”
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Research on the Evolution Characteristics of Building Space in the Central Urban Area of Tianjin Based on Multi-Source Data Collaboration: 2021–2024 by Yicheng Zhang, Guorui Chen, Xue Yang

“…This study addresses these gaps through an integrated framework combining point-of-interest kernel density analysis and satellite imagery segmentation (2021–2024 data). …”
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Non-invasive monitoring of microcirculation dynamics in hypovolemic shock: a novel application of diffuse correlation spectroscopy by Hiroki Matsushita, Koki Kurono, Mikie Nakabayashi, Kei Sato, Hidetaka Morita, Yuki Yoshida, Masafumi Fukumitsu, Kazunori Uemura, Toru Kawada, Masashi Ichinose, Yumie Ono, Keita Saku

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Analyzing Dispersion Characteristics of Fine Particulate Matter in High-Density Urban Areas: A Study Using CFD Simulation and Machine Learning by Daeun Lee, Caryl Anne M. Barquilla, Jeongwoo Lee

“…The resulting dataset trained five ML models with Extreme Gradient Boosting (XGBoost), achieving the highest accuracy (91–95%). …”
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Eye-Guided Multimodal Fusion: Toward an Adaptive Learning Framework Using Explainable Artificial Intelligence by Sahar Moradizeyveh, Ambreen Hanif, Sidong Liu, Yuankai Qi, Amin Beheshti, Antonio Di Ieva

“…We validate the system’s interpretability using Gradient-weighted Class Activation Mapping (Grad-CAM) and assess both classification performance and explanation alignment with expert annotations. …”
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Building Safer Social Spaces: Addressing Body Shaming with LLMs and Explainable AI by Sajedeh Talebi, Neda Abdolvand

“…Targeting Reddit’s anonymity-driven subreddits, the dataset fills a platform-specific gap. Integrating LLMs, LIME, and graph analysis, we develop scalable tools for real-time moderation to foster inclusive online spaces. …”
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