Trends in Autonomous Vehicle Technology: Hierarchical Clustering Using BERTopic with a Focus on Patent Data Analysis by Soyoung Kim, Junsung Park, Chang Geun Lee, Joon Woo Yoo, Youngju Cho, Jun Young Yoo, Hee Jun Park

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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

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VRU Safety at Road Intersections: An Ontology-Driven Digital Twin by Victor M. G. Martinez, Salim S. Mussi, Moises R. N. Ribeiro, Divanilson R. Campelo, Tereza C. Carvalho

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Le machine learning et les sciences sociales à l’épreuve des échelles de complexité algorithmique by Dominique Boullier, El Mahdi El Mhamdi

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Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study by Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah

“…This study aims to develop a novel decision-support ML model for classifying patients with biopsy-negative (cancer-free), clinically significant, and non-clinically significant prostate cancer across two prostate-specific antigen (PSA) cut-offs ≤ 10 ng/ml and > 10 ng/ml. …”
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Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

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Evaluation of SURUS: a named entity recognition NLP system to extract knowledge from interventional study records by Casper Peeters, Koen Vijverberg, Marianne Pouwer, Bart Westerman, Maikel Boot, Suzan Verberne

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Does machine learning outperform logistic regression in predicting individual tree mortality? by Aitor Vázquez-Veloso, Astor Toraño Caicoya, Felipe Bravo, Peter Biber, Enno Uhl, Hans Pretzsch

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Formation of a Strategy for Increasing the Efficiency of Operation of Distribution Electrical Grids at the Stage of Pre-Design Works by A. V. Zhurakhivskyi, Z. M. Bakhor, A. Ya. Yatseiko, V. H. Hapanovych

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Inflammatory and nutritional indexes as predictors of acute kidney injury in patients with Immunoglobulin A nephropathy: a retrospective study by Huimin Li, Chuyue Qian, Jingda Huang, Mindan Sun

“…They were randomly divided into a training set (n = 503) and a test set (n = 217) in a 7:3 ratio. Univariate and multivariate logistic regression analyses with backward selection were used to identify risk factors, resulting in multiple prediction models. …”
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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

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Wine price determinants. Is there a homogeneous international standard? by Tânia Gonçalves, João Rebelo, Lina Lourenço-Gomes, José Caldas

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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

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Ensemble-based customer churn prediction in banking: a voting classifier approach for improved client retention using demographic and behavioral data by Ruchika Bhuria, Sheifali Gupta, Upinder Kaur, Salil Bharany, Ateeq Ur Rehman, Seada Hussen, Ghanshyam G. Tejani, Pradeep Jangir

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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…We employed a two-stage machine learning approach: first applying Recursive Feature Elimination with multiple linear regression to identify core predictive items for total depression scores, followed by logistic regression for optimizing depression classification (CES-D ≥ 16). Model performance was systematically evaluated through discrimination (ROC analysis), calibration (Brier score), and clinical utility analyses (decision curve analysis), with additional validation using random forest and support vector machine algorithms across independent samples. …”
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Assessing the factors influencing the adoption of geothermal energy to support the national grid in emerging economies: Implications for sustainability by Md. Fahim Bin Alam, Saifur Rahman Tushar, Binoy Debnath, Amirhossein Taghipour, Hasan Dinçer, Abu Reza Md. Towfiqul Islam, A. B. M. Mainul Bari, Sadman Sakib Tushan

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Evaluation of hydro-geochemical processes controlling groundwater quality in Balkh center (Mazar-e-Sharif), northern Afghanistan by Asadullah Farahmand, Abdulhalim Zaryab, Nasrullah Ameri, Shakir Ali, Mohammad Naim Eqrar

“…Results: The results reveal that 1) The prevailing groundwater within the study area is predominantly characterized by Na-(Ca)-HCO3 and Ca-(Mg)-SO4 water types. 2) Physicochemical variables such as NO3−, F−, TDS, and SO42− exceeded the World Health Organization (WHO) safe limits in many wells. 3) Hydro-geochemical processes such as silicate weathering, cation exchange, and gypsum dissolution controls the groundwater chemistry. 4) Cl/Br ratios reveal, that high salinity may originate from evaporitic lacustrine and evaporite deposits and found to be localized in nature. 5) The Water Quality Index (WQI) classification suggests that approximately 60 % of the groundwater samples fall into poor to very poor water quality categories, highlighting substantial public health concerns. …”
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Evaluation of the long-term effectiveness of cardiac resynchronization therapy by T. V. Chumarnaya, T. A. Lyubimtseva, S. I. Solodushkin, V. K. Lebedeva, D. S. Lebedev, O. E. Solovieva

“…For the obtained clusters, we found cutoff values for LV reverse remodeling parameters, which can be used as criteria for response to therapy.The study identified the most informative time frames for assessing the postoperative CRT effectiveness 1, 2, 3 years after the surgery. At the same time, the clinical response to therapy is manifested earlier in comparison with the reverse LV remodeling.Despite the high divisibility of patients into responders and non-responders, predictive models of CRT effectiveness created using the available data from standard diagnostic protocols for heart failure patients have insufficient accuracy to be used for making decisions on therapy appropriateness. …”
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Development of Artificial Intelligence-Based Programs for the Diagnosis of Myocarditis in COVID-19 Using Chest Computed Tomography Data» by Ievgen A. Nastenko, Maksym O. Honcharuk, Vitalii O. Babenko, Mykola I. Lynnyk, Viktoria I. Ignatieva, Vitalii A. Yachnyk

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Agentic LLM-based robotic systems for real-world applications: a review on their agenticness and ethics by Emmanuel K. Raptis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos, Elias B. Kosmatopoulos

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