Sustainable project choice: Integrating Must-Be kano and fuzzy logic for optimal project selection by Vikas Swarnakar, Raed Jaradat, Malik Khalfan, Maher Maalouf, Abdelrahman E.E. Eltoukhy, Niamat Ullah Ibne Hossain

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Machine learning prediction of breast cancer local recurrence localization, and distant metastasis after local recurrences by Kristóf Attila Kovács, Csaba Kerepesi, Dalma Rapcsák, Lilla Madaras, Ákos Nagy, Anikó Takács, Magdolna Dank, Gyöngyvér Szentmártoni, Attila Marcell Szász, Janina Kulka, Anna Mária Tőkés

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Ultrasound derived deep learning features for predicting axillary lymph node metastasis in breast cancer using graph convolutional networks in a multicenter study by Enock Adjei Agyekum, Wentao Kong, Doris Nti Agyekum, Eliasu Issaka, Xian Wang, Yong-zhen Ren, Gongxun Tan, Xuan Jiang, Xiangjun Shen, Xiaoqin Qian

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Multi-Stage Operational Resilience Metric-Driven Optimal Service Restoration in DER-Rich Power Distribution Systems by Samridhi Sajwan, Bijaya Ketan Panigrahi, Anurag K. Srivastava

“…However, distributed energy resources (DERs) have emerged as a crucial element for resilient distribution systems, but their integration introduces greater variability in operational decision-making. This paper proposes a novel integrated resilience assessment metric (IRAM) to support real-time operations in DER-rich distribution systems. …”
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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…This handbook facilitates contingency planning as well as the development and use of early warning and response systems for dengue fever epidemics, by identifying decision-making processes that contribute to the success or failure of dengue surveillance, as well as triggers that initiate effective responses to incipient outbreaks.…”
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FaN-REMs: Fair and Normalized Retrieval Evaluation Metrics for Learning Retrieval Systems by Amar Jaiswal, Mohit Kumar, Ajeet Ram Pathak, Kassaye Yitbarek Yigzaw

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Aqua-MC as a simple open access code for uncountable runs of AquaCrop by Vahid Adabi, Hadi Ramezani Etedali, Asghar Azizian, Faraz Gorginpaveh, Ali Salem, Ahmed Elbeltagi

“…Abstract Understanding uncertainty in crop modeling is essential for improving prediction accuracy and decision-making in agricultural management. Monte Carlo simulations are widely used for uncertainty and sensitivity analysis, but their application to closed-source models like AquaCrop presents significant challenges due to the lack of direct access to source code. …”
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A Hybrid LSTM-GRU Model for Stock Price Prediction by Amirfarhad Farhadi, Azadeh Zamanifar, Amir Alipour, Alireza Taheri, Mohammad Asadolahi

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NeuroFuzzXAI: A Hybrid Artificial Intelligence Framework for Epileptic Seizure Detection by Flavia COSTI, Emanuel COVACI, Ovidiu ROMAN, Darian ONCHIS

“…The objective is to enhance transparency in decision-making by identifying key EEG features and providing an interpretable risk assessment. …”
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Visual‐Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning by Marta Zaniolo, Meagan S. Mauter, Sarah M. Fletcher

“…In this work, we fill this gap by proposing Visual‐Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. …”
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Pooled prevalence and determinants of household satisfaction with the community-based health insurance (CBHI) scheme in Ethiopia: a systematic review and meta-analysis by Getasew Berhanu, Yodit Abebe, Gizaw Sisay, Kassahun Animut

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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…In the context of rapidly evolving geospatial technologies, this study provides a comprehensive review of GIS model integration and service composition, emphasizing their critical roles in enhancing spatial analysis accuracy, decision-making efficiency, and cross-domain interoperability. …”
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Advancing the role of real-world evidence in comparative effectiveness research by Monica Daigl, Seye Abogunrin, Felipe Castro, Sarah F McGough, Rachele Hendricks Sturrup, Cornelis Boersma, Keith R Abrams

ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP by Yao Rao, Lilian Zhang, Lutao Gao, Shuran Wang, Linnan Yang

“…All models were trained and evaluated using five repeated five-fold cross-validation, and their performance was assessed based on both predictive accuracy and computational efficiency. …”
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Real-Time Telemedical Oversight Improves Prehospital Stroke Metrics: A Five-Year Cohort Study by Ponlawat Kanchayawong, Kasamon Aramvanitch, Chaiyaporn Yuksen, Satariya Trakulsrichai, Pungkava Sricharoen, Sureerat Suwatcharangkoon, Patcharaporn Sirintaranont, Jesada Keandoungchun, Promphet Nuanprom, Chetsadakon Jenpanitpong, Suthap Jaiboon

“… Introduction: By enabling direct consultation with neurologists, Real-Time Telemedical Oversight (ReTMO) can facilitate rapid stroke assessment and decision-making. This study aimed to assess the efficacy of prehospital stroke management before and after ReTMO implementation. …”
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Democratising complex system modelling by Anabele-Linda Pardi, Elizaveta Burina

“…Abstract In the contemporary context of an acute need for sustainability and swift response to imminent crises such as global warming, pandemics and economic system disruptions, the focus on responsible decision making, ethical risk assessment and mitigation at all organizational levels is an overarching goal. …”
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CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space by Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit

“…CIME4R aids decision-making through the interaction between humans and AI by combining the strengths of expert experience and high computational precision. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Obtained results suggest that the adoption of DL models in healthcare could aid in diagnostic assistance and decision-making during clinical practice. Funding: This work was supported by FAPESP (2022/13069-8, 2022/07276-0, 2021/14585-7 and 2024/20694-1), CAPES, CNPq (307604/2023-3) and FAPEMIG.…”
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A Comprehensive Review of Deep Learning Applications in Cotton Industry: From Field Monitoring to Smart Processing by Zhi-Yu Yang, Wan-Ke Xia, Hao-Qi Chu, Wen-Hao Su, Rui-Feng Wang, Haihua Wang

“…Deep learning (DL), with its superior capabilities in data analysis, pattern recognition, and autonomous decision-making, offers transformative potential across the cotton value chain. …”
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Analisis Metode AHP dan Promethee pada Sistem Pendukung Keputusan Penilaian Kompetensi Soft Skills Karyawan by Yuminah yuminah, Rusydi Umar, Abdul Fadlil

“…There are several methods that can be used for decision making with various criteria including AHP and Promethee. …”
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