Does the therapeutic alliance process explain the results of the Egokitzen post-divorce intervention program? by Irati Alvarez, Marta Herrero, Ana Martínez-Pampliega

“…ObjectiveThe objective of this study was to explain the relationship between therapeutic alliance and the changes observed in the parents’ psychological symptomatology after participation in the Egokitzen program, analyzing the mediating role of emotion regulation.MethodsThe study involved 117 divorced parents and 40 therapists.ResultsIt has been observed that the early development and maintenance of the therapeutic alliance influence the parents’ psychological symptomatology after the intervention, through emotion regulation.ConclusionThe study reinforce the role of the therapeutic alliance as a determining factor in the success of group interventions. …”
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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…To address these limitations, this paper proposes the Privacy Preserving Federated Blockchain Explainable Artificial Intelligence Optimization (PPFBXAIO) framework, which integrates blockchain technology, Explainable AI (XAI), and optimization techniques to ensure privacy, traceability, and robustness in FL-based systems. …”
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Towards Transparent Deep Learning in Medicine: Feature Contribution and Attention Mechanism-Based Explainability by Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Niall Higgins, Juan D. Velásquez

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LC-LLM: Explainable lane-change intention and trajectory predictions with Large Language Models by Mingxing Peng, Xusen Guo, Xianda Chen, Kehua Chen, Meixin Zhu, Long Chen, Fei-Yue Wang

“…In this study, we address these challenges by proposing a Lane Change-Large Language Model (LC-LLM), an explainable lane change prediction model that leverages the strong reasoning capabilities and self explanation abilities of Large Language Models (LLMs). …”
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Beyond Performance: Explaining and Ensuring Fairness in Student Academic Performance Prediction with Machine Learning by Kadir Kesgin, Salih Kiraz, Selahattin Kosunalp, Bozhana Stoycheva

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Explainable AI supported hybrid deep learnig method for layer 2 intrusion detection by Ilhan Firat Kilincer

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Branch Drift: A Visually Explainable Metric for Consistency Monitoring in Collaborative Software Development by Karl Kegel, Sebastian Gotz, Uwe Assmann

“…The branch-drift is based on an intuitive and explainable geometric representation, easing the analysis of conflict patterns and outliers. …”
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Explainable AI for Sensor Signal Interpretation to Revolutionize Human Health Monitoring: A Review by Abdullah S. Alharthi, Ahmed Alqurashi, Turki Essa Alharbi, Mohammed M. Alammar, Nasser Aldosari, Houssem R. E. H. Bouchekara, Yusuf A. Sha'aban, Mohammad Shoaib Shahriar, Abdulrahman Al Ayidh

Subjects: “…Explainable AI human health…”
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How THC works: Explaining ligand affinity for, and partial agonism of, cannabinoid receptor 1 by Farsheed Shahbazi-Raz, Daniel Meister, Azam Mohammadzadeh, John Frederick Trant

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Leveraging Explainable Artificial Intelligence in Solar Photovoltaic Mappings: Model Explanations and Feature Selection by Eduardo Gomes, Augusto Esteves, Hugo Morais, Lucas Pereira

Subjects: “…explainable artificial intelligence…”
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Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods by Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake

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An Explainable LSTM-Based Intrusion Detection System Optimized by Firefly Algorithm for IoT Networks by Taiwo Blessing Ogunseyi, Gogulakrishan Thiyagarajan

Subjects: “…explainable artificial intelligence (XAI)…”
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Explainable Artificial Intelligence for Crowd Forecasting Using Global Ensemble Echo State Networks by Chamod Samarajeewa, Daswin De Silva, Milos Manic, Nishan Mills, Prabod Rathnayaka, Andrew Jennings

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The importance of political and religious affiliation in explaining county-level COVID-19 Vaccine Hesitancy by Declan R. Carroll, Stephen J. Conroy, Adriana Vamosiu

“…Abstract The authors use county-level data to test whether an array of socioeconomic, demographic, political and religious variables explain COVID-19 vaccination rates. Results presented here build upon previous investigations of COVID-19 vaccine hesitancy in different contexts and are largely consistent with those findings. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

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Arsenic Exposure During Pregnancy and Childhood: Factors Explaining Changes over a Decade by Paola Rubilar, Macarena Hirmas-Adauy, Mauricio Apablaza, Camila Awad, Xaviera Molina, María Pía Muñoz, Iris Delgado, Nicolás C. Zanetta-Colombo, Carla Castillo-Laborde, María Isabel Matute, Mauricio A. Retamal, Andrea Olea, Paulina Pino, Claudia González, Cristóbal Carvajal, Verónica Iglesias

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Structure and usage do not explain each other: an analysis of German word-initial clusters by Wiese Richard, Orzechowska Paula

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An XAI Approach to Melanoma Diagnosis: Explaining the Output of Convolutional Neural Networks with Feature Injection by Flavia Grignaffini, Enrico De Santis, Fabrizio Frezza, Antonello Rizzi

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A feature explainability-based deep learning technique for diabetic foot ulcer identification by Pramod Singh Rathore, Abhishek Kumar, Amita Nandal, Arvind Dhaka, Arpit Kumar Sharma

“…The DFU_XAI framework integrates explainability into AI-driven healthcare, enhancing trust and usability in clinical settings. …”
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Transparent and reliable construction cost prediction using advanced machine learning and explainable AI by Lifei Chen, Changyong Xu, Wei Hong Lim, Abhishek Sharma, Sew Sun Tiang, Kim Soon Chong, El-Sayed M. El-kenawy, Amel Ali Alhussan, Marwa M. Eid, Doaa Sami Khafaga

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