A Bias Injection Technique to Assess the Resilience of Causal Discovery Methods by Martina Cinquini, Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi, Riccardo Guidotti

“…Causal discovery (CD) algorithms are increasingly applied to socially and ethically sensitive domains. …”
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Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus by Yulan Lu, Chunhong Liu, Xiaoxia Pang, Xinghong Chen, Chunfang Wang, Huatuo Huang

“…Then, the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) were used as the other algorithms for screening candidate signature miRNA genes. …”
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Enhanced EKF and SVSF for state of charge estimation of Li‐ion battery in electric vehicle using a fuzzy parameters model by Meriem Ben Lazreg, Sabeur Jemmali, Bilal Manai, Mahmoud Hamouda

“…Moreover, the reduction of the maximum absolute error may reach 0.34% with the FP‐EKF, and 0.82% with the FP‐SVSF, compared to the same algorithms without the proposed FP method. …”
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Design Principles for Reinforcement Learning in Congestion Control Environments by Lincoln Kamau Kiarie, Mahsa Derakhshani, Konstantinos G. Kyriakopoulos

“…Recent years have seen growth in interest in applying RL to managing Congestion Control (CC) in computer networks, with the goal of handling diverse kinds of traffic that may be challenging for human-designed algorithms. …”
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Towards fairness-aware and privacy-preserving enhanced collaborative learning for healthcare by Feilong Zhang, Deming Zhai, Guo Bai, Junjun Jiang, Qixiang Ye, Xiangyang Ji, Xianming Liu

“…Abstract The widespread integration of AI algorithms in healthcare has sparked ethical concerns, particularly regarding privacy and fairness. …”
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Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication by Tong Wang, Yongzhe Zhou, Yunfeng Wang, Mengbo Tang

“…Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. …”
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An Introduction to B-Cell Epitope Mapping and In Silico Epitope Prediction by Lenka Potocnakova, Mangesh Bhide, Lucia Borszekova Pulzova

“…Advances in B-cell epitope mapping and computational prediction have yielded molecular insights into the process of biorecognition and formation of antigen-antibody complex, which may help to localize B-cell epitopes more precisely. …”
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Machine Learning Model for Detecting Attack in Service Supply Chain by ASMAU OYINLADE OLANIYI, O. A Ayeni, M. G. Adewunmi

“…The study employs machine learning methods to increase the detection of service supply chain attacks, including Decision Trees, Random Forest, and XGBoost algorithms. These models were assessed in accordance with accuracy, precision, recall, and the F1-score, with Random Forest topping the list with an accuracy of 96.1%, followed by Decision Trees with 95.0% accuracy and XGBoost with 94.7% accuracy. …”
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Kidney Diseases Classification using Hybrid Transfer-Learning DenseNet201-Based and Random Forest Classifier by Abdalbasit Mohammed Qadir, Dana Faiq Abd

“…There are several disease kinds in global populations that may be related to human lifestyles, social, genetic, economic, and other factors related to the nature of the country they live in. …”
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Free Vibration Analysis of Moderately Thick Rectangular Plates with Variable Thickness and Arbitrary Boundary Conditions by Dongyan Shi, Qingshan Wang, Xianjie Shi, Fuzhen Pang

“…The effectiveness and reliability of the presented solution are demonstrated by comparing the present results with those results published in the literatures and finite element method (FEM) data, and numerous new results for moderately thick rectangular plates with nonuniform thickness and elastic restraints are presented, which may serve as benchmark solution for future researches.…”
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Highly Robust Synthetic Aperture Radar Target Recognition Method Based on Simulation Data Training by Liping Hu, Canming Yao, Jian Huang, Jinfan Liu, Guanyong Wang

“…Sufficient synthetic aperture radar (SAR) data is the key element in achieving excellent target recognition performance for most deep learning algorithms. It is unrealistic to obtain sufficient SAR data from the actual measurements, so SAR simulation based on electromagnetic scattering modeling has become an effective way to obtain sufficient samples. …”
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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

“…Therefore, data related to human social life may tell us the increase or decrease in the number of confirmed COVID-19 cases. …”
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Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. …”
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A Mountain Summit Recognition Method Based on Improved Faster R-CNN by Yueping Kong, Yun Wang, Song Guo, Jiajing Wang

“…Traditional summit detection methods operate on handcrafted features extracted from digital elevation model (DEM) data and apply parametric detection algorithms to locate mountain summits. However, these methods may no longer be effective to achieve desirable recognition results in small summits and suffer from the objective criterion lacking problem. …”
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Artificial intelligence facilitates clinical management of epithelial dysplasia in multiple organs by Xin-Jia Cai

“…Digital pathology-based AI may prove useful in facilitating the clinical management of epithelial dysplasia in multiple organs. …”
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Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review by Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, Mathias Unberath

“…Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. …”
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Awareness and Perspectives on the Role of Artificial Intelligence in Primary Care: Survey of Rural and Urban Primary Care Physicians in Alberta, Canada by Jose Uriel Perez

“…This survey's findings may inform future research into the development and implementation of AI in primary care. …”
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Explainable data mining model for hyperinsulinemia diagnostics by Nevena Rankovic, Dragica Rankovic, Mirjana Ivanovic, Igor Lukic

“…Medical datasets are often highly imbalanced and may contain irrelevant features that hinder predictive performance. …”
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The role of TMEM119 in gastric adenocarcinoma and its specific effects on immunity by Yating Liu, Xin Yan, Caihao Qu, Futian Tang, Qian Wang, Yumin Li

“…Additionally, CIBERSORT and ESTIMATE algorithms were applied to examine the relationship between TMEM119 expression and tumour-infiltrating immune cells, as well as the tumour microenvironment. …”
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Data-driven decoding of quantum error correcting codes using graph neural networks by Moritz Lange, Pontus Havström, Basudha Srivastava, Isak Bengtsson, Valdemar Bergentall, Karl Hammar, Olivia Heuts, Evert van Nieuwenburg, Mats Granath

“…The results show that a purely data-driven approach to decoding may be a viable future option for practical quantum error correction, which is competitive in terms of speed, accuracy, and versatility.…”
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