Assessing the association between ADHD and brain maturation in late childhood and emotion regulation in early adolescence by Kristóf Ágrez, Pál Vakli, Béla Weiss, Zoltán Vidnyánszky, Nóra Bunford

“…Whether the difference between an individual’s brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual’s chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. …”
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Breast tumors from ATM pathogenic variant carriers display a specific genome-wide DNA methylation profile by Nicolas M. Viart, Anne-Laure Renault, Séverine Eon-Marchais, Yue Jiao, Laetitia Fuhrmann, Sophia Murat El Houdigui, Dorothée Le Gal, Eve Cavaciuti, Marie-Gabrielle Dondon, Juana Beauvallet, Virginie Raynal, Dominique Stoppa-Lyonnet, Anne Vincent-Salomon, Nadine Andrieu, Melissa C. Southey, Fabienne Lesueur

“…Moreover, using three different deep learning algorithms (logistic regression, random forest and XGBoost), we identified a set of 27 additional biomarkers predictive of ATM status, which could be used in the future to provide evidence for or against pathogenicity in ATM variant classification strategies. …”
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Intelligent error-proof logic multi-factor cooperative active optimization based on knowledge base and generative adversarial network by Jinming Liu, Sheng Yang, Dunlin Zhu, Tianyun Luo, Jinglong He, Shengyuan Li

“…Combining the logic rules given by the power system and the real-time operation parameters of the substation, the intelligent terminal is used to monitor the remote control information of the anti-misoperation latching device in real-time and the power equipment is controlled by remote control of the anti-misoperation latching device. Attribute reduction of the decision table uses a niche genetic algorithm to extract the intelligent anti-failure logic rule set. …”
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TPE-LCE-SHAP: A Hybrid Framework for Assessing Vehicle-Related PM2.5 Concentrations by Hamad Almujibah, Abdulrazak H. Almaliki, Caroline Mongina Matara, Adil Abdallah Mohammed Elhassan, Khalaf Alla Adam Mohamed, Mudthir Bakri, Afaq Khattak

“…This hybrid framework delivers robust predictive accuracy and actionable insights, making it a valuable tool for effective environmental management and policy making.…”
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Synthesis and characterization of machine learning designed TADF molecules by Weimei Shi, Yan Li, Ziying Zhang, Zheng Tan, Shiqing Yang

“…Theoretical validations, through quantum chemical calculations, corroborated the experimental findings, demonstrating the predictive power of our ML models. This interdisciplinary approach not only accelerates the pace of TADF molecule development but also provides a scalable framework for future material innovation especially in the OLED research field.…”
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Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…The testing dataset was used for models’ evaluation through its accuracy, sensitivity, specificity, positive and negative predictive values and area under the receiving-operating characteristic curve. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…One possible result of AI integration is the early detection of diseases, especially in rural locations where access to expert medical care is limited. Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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Empowering Sustainability: The Crucial Role of IoT-Enabled Distributed Learning Systems in Reducing Carbon Footprints by Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh

“…Key observations include, EnMS with IoT devices and automation offers smartness, they do not lead to a significant reduction in energy consumption. Moreover, these IoT devices and centralized learning consume more energy. …”
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Ultra-Low Dose Computed Tomography Imaging in Quantifying Bone Trauma and Disorders: A Cross-Sectional Study by Fariba Zarei, Seyedeh Marzieh Ahmadi, Saber Dehbani-Zadeh, Anahita Jafari, Vyas Akondi, Sabyasachi Chatterjee, Seyed Alireza Mirhosseini, Rezvan Ravanfar Haghighi

“…The sensitivity and specificity of ULD-CT images for bone trauma and disorders were 67%–95% and 100%, respectively, with about a 98% dose reduction.Conclusion: The ULD-CT protocol for bone imaging achieved a remarkable dose reduction, while the image quality was reported as acceptable. …”
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DCLTV: An Improved Dual-Condition Diffusion Model for Laser-Visible Image Translation by Xiaoyu Zhang, Laixian Zhang, Huichao Guo, Haijing Zheng, Houpeng Sun, Yingchun Li, Rong Li, Chenglong Luan, Xiaoyun Tong

“…Existing cross-modal image translation algorithms are plagued with issues, including difficult training and color bleeding. …”
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Comprehensive Evaluation of Techniques for Intelligent Chatter Detection in Micro-Milling Processes by Guilherme Serpa Sestito, Wesley Angelino De Souza, Alessandro Roger Rodrigues, Maira Martins Da Silva

“…The performance of several ML classifiers is compared in each feature reduction stage with the Deep Learning algorithm. The results discuss the need for applying complex algorithms since the accuracy and F1-score indices presented similar values regardless of the number of features. …”
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Computer-economical optimization method for solving inverse problems of determining electrophysical properties of objects in eddy current structroscopy by V. Ya. Halchenko, R. V. Trembovetska, V. V. Tychkov

“…The results confirmed the validity of a significant reduction in space without major loss of information. …”
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Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass by J. Meloche, N. R. Leroux, B. Montpetit, V. Vionnet, C. Derksen

“…<p>Snow water equivalent (SWE) retrieval from Ku-band radar measurements is possible with complex retrieval algorithms involving prior information on the snowpack microstructure and a microwave radiative transfer model to link backscatter measurements to snow properties. …”
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Framework for Personalizing Wearable Devices Using Real-Time Physiological Measures by Prakyath Kantharaju, Sai Siddarth Vakacherla, Michael Jacobson, Hyeongkeun Jeong, Meet Nikunj Mevada, Xingyuan Zhou, Matthew J. Major, Myunghee Kim

“…The third case study personalized gait parameters, specifically step frequency, using an electrocardiogram (ECG)-based cost function along with an optimization algorithm variant, resulting in a 43&#x0025; reduction in optimization time for one non-disabled subject. …”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar, Mohammed Yusuf Ansari, Ajay Vikram Singh, Shahab Uddin, Kirthi S. Prabhu, Sagnika Dash, Souhaila Al Khodor, Annalisa Terranegra, Matteo Avella, Sarada Prasad Dakua

“…Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

“…Through the integration of scalable deep learning models coupled with feature selection, we have developed a classification pipeline with high predictive power, which could be integrated into a high-throughput real-time IR imaging system. …”
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A Comprehensive Review of Thermal Management Methods and Ideal System Design for Improved Electric Vehicle Battery Pack Performance and Safety by M. Murugan, P. V. Elumalai, KCK Vijayakumar, M. Babu, K. Suresh Kumar, M. Ganesh, Liu Kuang, S. Prabhakar

“…This is shown through the industry's constant pursuit to develop in this critical area through the discovery of novel technologies, including predictive control algorithms and superior thermal materials. …”
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Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review by Natalie S Blencowe, Neil J Smart, George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway

“…Diagnostic accuracy of AI models, including reported sensitivity, specificity, predictive values, likelihood ratios and the area under the receiver operating characteristic curve will be examined and compared with standard practice. …”
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Advancing multidisciplinary management of pediatric hyperinflammatory disorders by Francesco La Torre, Giovanni Meliota, Adele Civino, Angelo Campanozzi, Valerio Cecinati, Enrico Rosati, Emanuela Sacco, Nicola Santoro, Ugo Vairo, Fabio Cardinale

“…Future research directions include the identification of predictive biomarkers, exploration of novel therapeutic targets, and development of evidence-based treatment protocols to enhance long-term outcomes in pediatric inflammatory diseases.…”
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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…The proposed model achieves a superior classification accuracy of 98.8%, significantly outperforming conventional CNN implementations in terms of both computational speed and predictive accuracy. These findings suggest that the developed system holds substantial potential for early, reliable, and cost-effective breast cancer screening in real-world clinical environments.…”
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