Impact of EU Laws on AI Adoption in Smart Grids: A Review of Regulatory Barriers, Technological Challenges, and Stakeholder Benefits by Bo Nørregaard Jørgensen, Saraswathy Shamini Gunasekaran, Zheng Grace Ma

“…The analysis delves into regulatory barriers such as data protection requirements, algorithmic transparency mandates, and liability concerns that can limit the scope and scale of AI deployment. …”
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Task shifting for non-communicable disease management in low and middle income countries--a systematic review. by Rohina Joshi, Mohammed Alim, Andre Pascal Kengne, Stephen Jan, Pallab K Maulik, David Peiris, Anushka A Patel

“…Factors such as training of NPHWs, provision of algorithms and protocols for screening, treatment and drug titration were the main enablers of the task-shifting intervention. …”
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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

“…Summaries generated by AI models offer new opportunities for analyzing machine-generated language and provide valuable data for studying how algorithms process, condense, and restructure human language.…”
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Generative Design-Driven Optimization for Effective Concrete Structural Systems by Hossam Wefki, Mona Salah, Emad Elbeltagi, Majed Alinizzi

“…This research introduces a parametric algorithmic model for the automated optimization of RC buildings with solid slab systems. …”
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Participatory science methods to monitor water quality and ground truth remote sensing of the Chesapeake Bay. by Patrick Neale, Shelby Brown, Tara Sill, Alison Cawood, Maria Tzortziou, Jieun Park, Min-Sun Lee, Beth Paquette

“…The Chesapeake Water Watch program seeks to enhance the monitoring of tributaries by developing and testing methods for volunteer scientists to easily measure chlorophyll, turbidity, and colored dissolved organic matter (CDOM) to inform Bay stakeholders and improve algorithms for analogous remote sensing (RS) products. …”
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Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

“…Using <i>R</i> and the <i>caret</i> package (version 6.0.94), we developed and compared several ML algorithms, validated using 10-fold cross-validation and optimized by grid search hyperparameter tuning. …”
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SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

“…Individual tree segmentation (ITS) from terrestrial laser scanning (TLS) point clouds is foundational for deriving detailed forest structural parameters, crucial for precision forestry, biomass calculation, and carbon accounting. Conventional ITS algorithms often struggle in complex forest stands due to reliance on heuristic rules and manual feature engineering. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…This study aims to develop artificial intelligence algorithms based on gait analysis, integrating sensor and computer vision (CV) data, to detect sarcopenia and CD. …”
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Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records by Elizabeth Ford, James Stone, James Stone, James Stone, Dominic Oliver, Dominic Oliver, Dominic Oliver, Benjamin Fell, Gloria Roque, Sam Robertson, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Kathryn Greenwood, Kathryn Greenwood

“…We developed new machine-learning NLP algorithms for diagnosis, symptom and substance use concepts by fine-tuning existing open-source transformer models. …”
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Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…Additionally, we identified three proteins that predict the presence of distant metastases among patients with LAC. …”
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Visible, near-infrared, and shortwave-infrared spectra as an input variable for digital mapping of soil organic carbon by Vahid Khosravi, Asa Gholizadeh, Radka Kodešová, Prince Chapman Agyeman, Mohammadmehdi Saberioon, Luboš Borůvka

“…Models were developed on environmental predictor covariates (EPCs) and thirty genetic algorithms (GA)-selected visible, near-infrared, and shortwave-infrared (VNIR–SWIR) wavelengths spectra, individually and combined. …”
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Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning by Leeran Talker, Cihan Dogan, Daniel Neville, Rui Hen Lim, Henry Broomfield, Gabriel Lambert, Ahmed Selim, Thomas Brown, Laura Wiffen, Julian Carter, Helen F. Ashdown, Gail Hayward, Elango Vijaykumar, Scott T. Weiss, Anoop Chauhan, Ameera X. Patel

“…This study’s aim was to use interpretable machine learning to diagnose COPD and assess severity using 75-second carbon dioxide (CO2) breath records captured with TidalSense’s N-TidalTM capnometer.Method For COPD diagnosis, machine learning algorithms were trained and evaluated on 294 COPD (including GOLD stages 1–4) and 705 non-COPD participants. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

“…By merging IoT technology with machine learning algorithms, smart farming is poised to enter a transformative phase, providing a scalable response to the pressing issues of global food security. …”
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Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning by Jinyu Zheng, Xiaoyi Xu, Xianguo Chen, Xianshuai Li, Miao Fu, Yiping Zheng, Jie Yang

“…Three machine learning algorithms—Random Forest, LASSO, and SVM-RFE—were applied to identify key hub genes. …”
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Cystic Fibrosis Newborn Screening: A Systematic Review-Driven Consensus Guideline from the United States Cystic Fibrosis Foundation by Meghan E. McGarry, Karen S. Raraigh, Philip Farrell, Faith Shropshire, Karey Padding, Cambrey White, M. Christine Dorley, Steven Hicks, Clement L. Ren, Kathryn Tullis, Debra Freedenberg, Q. Eileen Wafford, Sarah E. Hempstead, Marissa A. Taylor, Albert Faro, Marci K. Sontag, Susanna A. McColley

“…Newborn screening for cystic fibrosis (CF) has been universal in the US since 2010; however, there is significant variation among newborn screening algorithms. Systematic reviews were used to develop seven recommendations for newborn screening program practices to improve timeliness, sensitivity, and equity in diagnosing infants with CF: (1) The CF Foundation recommends the use of a floating immunoreactive trypsinogen (IRT) cutoff over a fixed IRT cutoff; (2) The CF Foundation recommends using a very high IRT referral strategy in CF newborn screening programs whose variant panel does not include all CF-causing variants in CFTR2 or does not have a variant panel that achieves at least 95% sensitivity in all ancestral groups within the state; (3) The CF Foundation recommends that CF newborn screening algorithms should not limit <i>CFTR</i> variant detection to the F508del variant or variants included in the American College of Medical Genetics-23 panel; (4) The CF Foundation recommends that CF newborn screening programs screen for all CF-causing <i>CFTR</i> variants in CFTR2; (5) The CF Foundation recommends conducting <i>CFTR</i> variant screening twice weekly or more frequently as resources allow; (6) The CF Foundation recommends the inclusion of a <i>CFTR</i> sequencing tier following IRT and <i>CFTR</i> variant panel testing to improve the specificity and positive predictive value of CF newborn screening; (7) The CF Foundation recommends that both the primary care provider and the CF specialist be notified of abnormal newborn screening results. …”
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Construction and interpretation of tobacco leaf position discrimination model based on interpretable machine learning by Ranran Kou, Cong Wang, Jinxia Liu, Ran Wan, Zhe Jin, Le Zhao, Youjie Liu, Junwei Guo, Feng Li, Hongbo Wang, Song Yang, Cong Nie

“…In recent years, near-infrared (NIR) spectroscopy combined with algorithmic models has emerged as a popular method for identifying the tobacco leaf position. …”
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A multicenter pragmatic implementation study of AI-ECG-based clinical decision support software to identify low LVEF: Clinical trial design and methods by Francisco Lopez-Jimenez, Heather M. Alger, Zachi I. Attia, Barbara Barry, Ranee Chatterjee, Rowena Dolor, Paul A. Friedman, Stephen J. Greene, Jason Greenwood, Vinay Gundurao, Sarah Hackett, Prerak Jain, Anja Kinaszczuk, Ketan Mehta, Jason O'Grady, Ambarish Pandey, Christopher Pullins, Arjun R. Puranik, Mohan Krishna Ranganathan, David Rushlow, Mark Stampehl, Vinayak Subramanian, Kitzner Vassor, Xuan Zhu, Samir Awasthi

“…Background: Artificial intelligence (AI) enabled algorithms can detect or predict cardiovascular conditions using electrocardiogram (ECG) data. …”
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Regulatory Framework of the Conduct of Forensic Construction Examination by A. A. Revunov

“…In order to improve the current situation concerning the regulation of forensic construction and technical examinations, the following measures have been proposed: revision and improvement of their methodological, theoretical, and legal foundations, in-depth analysis of the content of urban planning legislation from the point of view of requirements mandatory for application by a forensic expertbuilder, specifying the limits of an expert’s competence, the formation of unified algorithms and forms of presenting research, the development of sub-theories on the legal and organizational support of the nonstate forensic activity, the active involvement of research institutions and higher educational institutions in the conduct of expert examinations.…”
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How does artificial intelligence shape the productivity and quality of research in business studies? A systematic literature review and future research framework by Sugandha Agarwal, Qian Long Kweh, Dima Jamali, Walton Wider, Syed Far Abid Hossain, Muhammad Ashraf Fauzi

“…Moreover, policymakers and managers should educate themselves and their teams about AI to maximize its benefits while minimizing associated risks. …”
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Microcontroller-Based Platform for Lithium-Ion Battery Charging and Experimental Evaluation of Charging Strategies by Laurentiu Marius Baicu, Mihaela Andrei, Bogdan Dumitrascu

“…Future enhancements may include the integration of adaptive algorithms based on internal resistance and temperature, enabling smarter and more efficient charging.…”
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