Optimization of Diagnostic and Treatment Tactics Regarding Impacted Lower Third Molars with the Employment of Author’s Program of Computer Modelling by Vares Y., Kyyak S.

“…Planning of the operation of atypical removal of the lower third molars requires the consideration of a number of general-somatic and local clinical characteristics, the ability to interpret the anatomical structure of the tooth and the adjacent structures on X-ray diffraction and computer tomography, prediction of all possible complications for the safe operation and avoiding complications in the postoperative period, possession with a variety of surgical techniques. …”
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A Refined Terrace Extraction Method Based on a Local Optimization Model Using GF-2 Images by Guobin Kan, Jie Gong, Bao Wang, Xia Li, Jing Shi, Yutao Ma, Wei Wei, Jun Zhang

“…Moreover, leveraging deep learning (DL) models with local adaptive improvements can further enhance the accuracy of interpretation by exploring latent information. …”
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Assessment of Artificial Intelligence-Driven Fitness and Health Management Programs for Adolescents Using the SuperHyperSoft Set Framework by Di Wu, Ali Khatibi, Jacquline Tham

“…Through a real-world case study, we demonstrate how the model supports a more nuanced and interpretable evaluation. …”
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Cost-effectiveness and benefit-risk of rotavirus vaccination in Afghanistan: a modelling analysis informed by post-licensure surveillance by Palwasha Anwari, Frédéric Debellut, Sardar Parwiz, Clint Pecenka, Andrew Clark

“…Methods We used a static cohort model with a finely disaggregated age structure (weeks of age < 5 years) to assess the use of ROTARIX (1-dose vial) over a seven-year period (2018–2024) in Afghanistan. …”
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Advancing the selection of implementation science theories, models, and frameworks: a scoping review and the development of the SELECT-IT meta-framework by Guillaume Fontaine, Meagan Mooney, Joshua Porat-Dahlerbruch, Katherine Cahir, Moriah Ellen, Anne Spinewine, Natalie Taylor, Rachael Laritz, Ève Bourbeau-Allard, Jeremy M. Grimshaw

“…Seven distinct purposes were identified: (1) enhancing conceptual clarity, (2) anticipating change and guiding inquiry, (3) guiding the implementation process, (4) guiding identification of determinants, (5) guiding design and adaptation of strategies, (6) guiding evaluation and causal explanation, and (7) guiding interpretation and dissemination. Additionally, 24 TMF attributes were grouped into five domains: clarity and structure, scientific strength and evidence, applicability and usability, equity and sociocultural responsiveness, and system and partner integration. …”
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Enhancing Magnetotelluric Data Quality Using Deep Learning-Based Denoising Models: A Study of CNN and LSTM by Widya Utama, Maman Hermana, Dwa D. Warnana, Wien Lestari, Muhammad N. A. Zakariah, Sherly A. Garini, Rista F. Indriani, Dhea P. Novian Putra, M Ulin Nuha Abduh, Alif N. F. Insani, Dandi Syahtia Pratama, Khairul Arifin Mohd Noh, Abdul Halim Abdul Latiff

“…To address this critical issue, this study develops denoising models based on Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) to enhance the quality of MT signals while preserving their original structure. …”
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Theoretical analysis of adsorption of various compounds onto hydrophilic and hydrophobic silicas compared to activated carbons by V. M. Gun'ko

“… The aim of this study was to analyze various theoretical models (clusters, systems with periodic boundary conditions) and methods, which could be applied to investigate the adsorption phenomena and for better interpretation of the experimental data. …”
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Progress in digital and intelligent technologies for complex giant systems in green coal development by Guofa WANG, Jianzhong ZHANG, Zaibin LIU, Yihui PANG, Tong WANG, Cong SANG

“…We have proposed intelligent control methods for mining systems under the intelligent logic model framework, intelligent mining complex scene comprehensive mining equipment group posture recognition methods, global optimal planning strategies and collaborative control methods, equipment health status recognition and fault diagnosis methods; Interpreting the concept of “transparent geology”, proposing a path for transparent geological security technology, developing geological transparency technologies such as fine geophysical exploration and drilling, dynamic monitoring of surrounding rock conditions, multi-source high-precision data collection, multi-source heterogeneous data fusion and interpretation, innovating geological digitalization technologies such as static geological modeling, dynamic geological modeling, precise geological security of working faces, multi-source geological data interpretation and fusion, multi-attribute dynamic high-precision modeling, synchronous mapping of geological information, mining information modeling, etc., analyzing the application value of “transparent geology” technology in underground resource development geological structure exploration degree, revealing the physical and mechanical properties of coal and rock, “three field” changes, hidden disaster factor prediction, etc; Analyzed green mining technologies, including green sedimentation reduction and water conservation mining technologies, as well as well as collaborative management and ecological restoration technologies above and below the well; Case analysis was conducted around three technologies: intelligent mining, transparent geology, and green mining. …”
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Prediction of UHPC mechanical properties using optimized hybrid machine learning model with robust sensitivity and uncertainty analysis by ZhiGuang Zhou, Jagaran Chakma, Md Ahatasamul Hoque, Vaskar Chakma, Asif Ahmed

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Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework by Narayanaswamy Sridevi Kottapalli, Muniswamy Rajanna

“…The Non-dominated Sorting Genetic Algorithm II is employed to identify Pareto-optimal solutions, balancing accuracy, efficiency, and interpretability. The framework is evaluated using the GLUE benchmark dataset with BERT-based tokenization for structured input representation. …”
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Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course by Sujan Ghimire, Shahab Abdulla, Lionel P. Joseph, Salvin Prasad, Angela Murphy, Aruna Devi, Prabal Datta Barua, Ravinesh C. Deo, Rajendra Acharya, Zaher Mundher Yaseen

“…This study introduces an interpretable hybrid model, optimised through Tree-structured Parzen Estimation (TPE) and Support Vector Regression (SVR), to predict overall scores (OT) utilising five assignments and one examination mark as predictors. …”
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Exploring Students’ Learning Experiences Under the China–Korea Cooperative Teaching Model: A Positive Psychology Perspective by Lei Song, Zhenzhen Huang, Luhao Cao, Shanshan Yang

“…Based on the theory of learning experiences and the Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment (PERMA) model, this research aims to interpret the learning experiences of students majoring in Animation under the China–Korea cooperative teaching model from a perspective of positive psychology. …”
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Influencing factors systems analysis for the cultivated land protection policies implementation in China: a hybrid DEMATEL-ISM-MICMAC model by Yanwei Zhang, Xinhai Lu

“…The research methods include Decision-making Trial and Evaluation Laboratory (DEMATEL), Interpretative Structural Modeling Method (ISM) and Matrix Impacts Cross-Reference Multiplication Applied to A Classification (MICMAC). …”
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Comparative analysis of machine learning techniques in metabolomic-based preterm birth prediction by Ying-Chieh Han, Jane Shearer, Chunlong Mu, Donna M. Slater, Suzanne C. Tough, Gavin E. Duggan

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Forgotten Victims of War: A Rapid Review of Counseling Needs and a Proposed Intervention Model for Civilian Survivors by Runna Alghazo, Paola Premuda-Conti

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Towards Omni-Font Optical Character Recognition (OCR) for Persian script using the YOLO object detection model by Mojtaba Gandomkar, Sahar Khoramipour

“…Optical Character Recognition (OCR), especially for scripts with complex structures like Persian script, faces significant challenges in interpreting nuanced characters and contextual variations. …”
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Presenting the AI models in predicting the settlement of earth dams using the results of spatiotemporal clustering and k-means algorithm by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

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Comparing the Effectiveness of Machine Learning and Deep Learning Models in Student Credit Scoring: A Case Study in Vietnam by Nguyen Thi Hong Thuy, Nguyen Thi Vinh Ha, Nguyen Nam Trung, Vu Thi Thanh Binh, Nguyen Thu Hang, Vu The Binh

“…Gradient Boosting was effective in recall-oriented tasks, and support vector machine demonstrated strong precision for the positive class, although its recall was lower compared to other models. The study highlights the importance of aligning model selection with specific application goals, such as prioritizing accuracy, recall, or interpretability. …”
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A qualitative study of how clinicians reach agreement in perioperative pathway development: the Consensus Model for Standardising Healthcare by Lisa Pagano, Janet C. Long, Emilie Francis-Auton, Andrew Hirschhorn, Gaston Arnolda, Jeffrey Braithwaite, Mitchell N. Sarkies

“…Data were analysed using coding, constant comparison, detailed memo writing and data interpretation. Results Seven individual and contextual factors crucial for building consensus, and eight mechanisms for reaching agreement were identified and integrated into a conceptual model. …”
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Can open source large language models be used for tumor documentation in Germany?—An evaluation on urological doctors’ notes by Stefan Lenz, Arsenij Ustjanzew, Marco Jeray, Meike Ressing, Torsten Panholzer

“…It involves reading the textual patient documentation and filling in forms in dedicated databases to obtain structured data. Advances in information extraction techniques that build on large language models (LLMs) could have the potential for enhancing the efficiency and reliability of this process. …”
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