Artificial intelligence in drug development: reshaping the therapeutic landscape by Sarfaraz K. Niazi, Zamara Mariam

“…Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered “black boxes,” making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. …”
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Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves by Trong Tu

“…This research remarks the fundamentals of the experimental validation and further refinement of these control algorithms to adapt to various driving conditions and vehicle models, ultimately aiming to transition these optimized controllers from theoretical frameworks to practical, real-world applications. …”
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Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction by Bo Sun

“…The study investigates the revolutionary possibilities of Gated Recurrent Neural Networks (GRNN) to improve ELL-tailored training. The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. …”
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Generative design for architectural spatial layouts: a review of technical approaches by Shurui Yan, Chen Wu, Yixin Zhang

“…Additionally, improving computational efficiency makes knowledge-driven methods, such as heuristic algorithms, more user-friendly. …”
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AI-Driven Framework for Evaluating Climate Misinformation and Data Quality on Social Media by Zeinab Shahbazi, Rezvan Jalali, Zahra Shahbazi

“…Data quality is defined using key dimensions of credibility, accuracy, relevance, and sentiment polarity, and a pipeline is developed using transformer-based NLP models, sentiment classifiers, and misinformation detection algorithms. …”
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MultiModal Ensemble Approach Leveraging Spatial, Skeletal, and Edge Features for Enhanced Bangla Sign Language Recognition by Khan Abrar Shams, Md. Rafid Reaz, Mohammad Ryan Ur Rafi, Sanjida Islam, Md. Shahriar Rahman, Rafeed Rahman, Md. Tanzim Reza, Mohammad Zavid Parvez, Subrata Chakraborty, Biswajeet Pradhan, Abdullah Alamri

“…We introduce three image pre-processing techniques alongside three CNN models. The CNN models are combined using nine distinct ensemble meta-learning algorithms, with five of them being modifications of averaging and voting techniques. …”
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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects by Maryam Yeganegi, Mahsa Danaei, Sepideh Azizi, Fatemeh Jayervand, Reza Bahrami, Seyed Alireza Dastgheib, Heewa Rashnavadi, Ali Masoudi, Amirmasoud Shiri, Kazem Aghili, Mahood Noorishadkam, Hossein Neamatzadeh

“…AI integration with genomic analysis has identified key biomarkers associated with NTDs, such as Growth Associated Protein 43 (GAP43) and Glial Fibrillary Acidic Protein (GFAP), with logistic regression models achieving 86.67% accuracy. Current AI-assisted ultrasound technologies have improved diagnostic accuracy, yielding sensitivity and specificity rates of 88.9% and 98.0%, respectively, compared to traditional methods with 81.5% sensitivity and 92.2% specificity. …”
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Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort by Kyndaron Reinier, Harpriya S. Chugh, Audrey Uy-Evanado, Elizabeth Heckard, Marco Mathias, Nichole Bosson, Vinicius F. Calsavara, Piotr J. Slomka, David A. Elashoff, Alex A.T. Bui, Sumeet S Chugh

“…Conclusions: The OSCAR cohort will provide a large, diverse dataset and adjudicated SCA outcomes to facilitate the derivation and testing of risk prediction models for incident SCA.…”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The research not only deepens the understanding of emotion classification algorithms but also provides valuable perspectives for their application in crucial areas such as mental health and personalized medical assistance. …”
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Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. by Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E Urai, C Daniel Salzman, International Brain Laboratory, John P Cunningham, Liam Paninski

“…We also show how the behavioral features produced by our model improve the precision and interpretation of these downstream analyses compared to using the outputs of either fully supervised or fully unsupervised methods alone.…”
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Hybrid Filtering Technique for Accurate GNSS State Estimation by Jahnvi Verma, Nischal Bhattarai, Thejesh N. Bandi

“…We demonstrate that this hybrid method outperforms classical algorithms both in terms of accuracy and flexibility for easier implementation, showing better than 30% improvement in the variance of the horizontal position for the simulated as well as the real-world dynamic receiver dataset. …”
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5G OFDM channel estimation method based on complex-valued generative adversarial network by LU Yuanzhi, WEI Xianglin, YU Long, YAO Changhua

“…Channel estimation methods based on least square (LS) and minimum mean square error (MMSE) effectively utilize the system’s sparsity, but LS algorithms face low computational precision, while MMSE algorithms suffer from high computational complexity. …”
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Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…We examine various metaheuristic algorithms employed and, in particular, their effectiveness in improving model performance across diverse applications. …”
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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

“…Statistically significant differences were observed across models and between models and real-world demographics. …”
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Applying Neural Networks to Analyse Inflammatory, Sociodemographic, and Psychological Factors in Non-Melanoma Skin Cancer and Colon Cancer: A Statistical and Artificial Intelligenc... by Răzvan Mercuţ, Marius Eugen Ciurea, Emil Tiberius Traşcă, Mihaela Ionescu, Maria Filoftea Mercuţ, Patricia Mihaela Rădulescu, Cristina Călăraşu, Liliana Streba, Alin Gabriel Ionescu, Dumitru Rădulescu

“…This study aims to develop a comprehensive patient profiling model by comparing non-melanoma skin cancer (NMSC) and colorectal cancer (CRC). …”
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Transductive Radar Clutter Segmentation Network for Ionospheric Inhomogeneity Clutter Suppression by Yuanbiao Li, Lei Yu, Yinsheng Wei

“…Experiments demonstrate the effectiveness of TRCS-Net in improving clutter suppression performance compared to individual algorithms, leveraging transductive transfer learning and simulation data.…”
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Exploration and Construction of Personalized Customization Mode in Modern Fashion Design by Sun Huaiqun

“…By analyzing the advantages of this model in meeting personalized consumer needs, improving production efficiency, and promoting green design and sustainable development, this article further proposes specific suggestions for technology optimization, process simplification, and user experience improvement. …”
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Carbon co-benefits of digital economy and green finance: empirical evidence from China by Yayun Ren, Xiaohang Xu, Yantuan Yu, Zhenhua Zhang

“…These findings are robust across various validation tests, including time-placebo test, alternative model specification, and double machine learning algorithms. …”
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A lightweight knowledge graph-driven question answering system for field-based mineral resource survey by Mingguo Wang, Chengbin Wang, Jianguo Chen, Bo Wang, Wei Wang, Xiaogang Ma, Jiangtao Ren, Zichen Li, Yicai Ye, Jiakai Zhang, Yue Wang

“…The results also suggest that further studies on geoscience pre-trained models, an informative library of question templates, and multimodal knowledge graphs are necessary to improve the performance of the knowledge graph-driven question-answering system.…”
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DMP-PUNet: A novel network for two-dimensional InSAR phase unwrapping under severe noise and complex fringes conditions by Yu Chen, Shuai Wang, Yandong Gao, Yanjian Sun, Jinqi Zhao, Kun Tan, Peijun Du

“…This simulation, combined with quasi-real interferometric phase data obtained from DEM inversion algorithms, forms the comprehensive training dataset. …”
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