Advanced Learning Technologies for Intelligent Transportation Systems: Prospects and Challenges by Ruhul Amin Khalil, Ziad Safelnasr, Naod Yemane, Mebruk Kedir, Atawulrahman Shafiqurrahman, NASIR SAEED

“…In addition to shedding light on the state-of-the-art DL algorithms, we also explore potential applications of DL and large language models (LLMs) in ITS, including traffic flow prediction, vehicle detection and classification, road condition monitoring, traffic sign recognition, and autonomous vehicles. …”
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The colours of the ocean: using multispectral satellite imagery to estimate sea surface temperature and salinity on global coastal areas, the Gulf of Mexico and the UK by Solomon White, Tiago Silva, Laurent O. Amoudry, Evangelos Spyrakos, Adrien Martin, Adrien Martin, Encarni Medina-Lopez

“…This study presents a methodology for extracting SST and SSS using machine learning algorithms trained with in-situ and multispectral satellite data. …”
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Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy by Lakshay Arora, Sunil K. Singh, Sudhakar Kumar, Hardik Gupta, Wadee Alhalabi, Varsha Arya, Shavi Bansal, Kwok Tai Chui, Brij B. Gupta

“…This framework takes help from the EfficientNet Machine Learning algorithms and employing advanced CNN layering techniques. …”
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Hybrid Active-Passive Shielding of Magnetic Field of Overhead Power Lines with Triangular Phase Conductors Arrangements by Kuznetsov B.I., Kutsenko A.S., Nikitina T.B., Bovdui I.V., Chunikhin K.V., Dobrodeyev P.N.

“…The solution of a multicriteria game is found on the basis of algorithms for optimizing a multi-swarm of particles from Pareto optimal solutions, taking into account binary preference relations. …”
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Organization experience of diagnostic and medicosocial services for patients with Charcot—Marie—Tooth disease in Krasnoyarsk region by E. V. Glushchenko, N. A. Shnayder, E. A. Kantimirova, E. A. Kozulina, M. I. Voevoda, V. N. Maksimov, A. A. Allakhverdyan

“…Goal of the study was the development of evidence-based diagnostic and treatment algorithms using patients with CMT (for example, in Krasnoyarsk Territory).Materials and methods: A total of 324 people. …”
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Emerging analytical frontiers in microplastic detection: From spectroscopy to smart sensor technologies by Jen-Tai Lin, Ya-Ping Chung, Yen-Yi Lee, Tong-Lin Wu, Thao Thi Thu Huynh, Phung Thi Nguyen, Mei-Jou Lu, Bo-Wun Huang, Balasubramanian Sriram, Sea-Fue Wang, Guo-Ping Chang-Chien, Sakthivel Kogularasu, Wan-Ching Lin

“…Additionally, the integration of artificial intelligence and machine learning algorithms with high-dimensional spectral and electrochemical datasets is discussed as a transformative approach for enhancing classification accuracy, reducing analysis time, and facilitating automated detection. …”
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Combined influence of crushed brick powder and recycled concrete aggregate on the mechanical, durability and microstructural properties of eco-concrete: An experimental and machine... by Md. Habibur Rahman Sobuz, Mahmudur Hossain Khan, Md. Rakibul Islam, Md. Kawsarul Islam Kabbo, Abdullah Alzlfawi, M Jameel, Md. Munir Hayet Khan

“…Additionally, the study evaluates machine learning algorithms such as extreme gradient boosting (XG Boost), random forest (RF), and bagging model (BAG) for predicting the mechanical strength of concrete specimens. …”
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Design and refinement of a clinical trial staffing model within the evolving landscape of oncology clinical trials by Ellen Siglinsky, Hannah Phan, Silviya Meletath, Amber Neal, David E. Gerber, Asal Rahimi, Erin L. Williams

“…Methods: To address individual protocol acuity, the model's algorithms include metrics to account for visit frequency, and the quantity, and types of research-related procedures. …”
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Early detection of Cercospora beticola and powdery mildew diseases in sugar beet using uncrewed aerial vehicle-based remote sensing and machine learning by Koç Mehmet Tuğrul, Rıza Kaya, Kemal Özkan, Merve Ceyhan, Uğur Gürel, Fatih Yavuz Fidantemiz

“…Additionally, the study demonstrated that early detection of diseases is possible using K-nearest neighbors and logistic regression algorithms, exhibiting high discrimination and predictive accuracy.…”
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Recognition and management of auditory verbal hallucinations in borderline personality disorder by M. B. A. Niemantsverdriet, M. B. A. Niemantsverdriet, C. W. Slotema, C. W. Slotema, I. H. A. Franken, J. Brandsma, M. J. P. M. Verbraak, M. L. Deen, J. D. Blom, J. D. Blom, J. D. Blom, M. Van der Gaag

“…Further research is needed to develop algorithms to optimize doses in individual patients, to develop treatment guidelines, and to explore the effects of nonpharmacological treatments.…”
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Machine learning predictive model for aspiration risk in early enteral nutrition patients with severe acute pancreatitis by Bo Zhang, Huanqing Xu, Qigui Xiao, Wanzhen Wei, Yifei Ma, Xinlong Chen, Jingtao Gu, Jiaoqiong Zhang, Lan Lang, Qingyong Ma, Liang Han

“…Subsequently, we used six machine learning algorithms and the model was validated by the area under the curve. …”
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Utilizing machine learning techniques to identify severe sleep disturbances in Chinese adolescents: an analysis of lifestyle, physical activity, and psychological factors by Lirong Zhang, Shaocong Zhao, Wei Yang, Zhongbing Yang, Zhi’an Wu, Hua Zheng, Mingxing Lei, Mingxing Lei, Mingxing Lei

“…Participants in the training set were utilized to establish models, and the logistic regression (LR) and five machine learning algorithms, including the eXtreme Gradient Boosting Machine (XGBM), Naïve Bayesian (NB), Support Vector Machine (SVM), Decision Tree (DT), CatBoosting Machine (CatBM), were utilized to develop models. …”
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Unsupervised Machine Learning for Classifying CHIME Fast Radio Bursts and Investigating Empirical Relations by Da-Chun Qiang, Jie Zheng, Zhi-Qiang You, Sheng Yang

“…By employing Uniform Manifold Approximation and Projection for dimensionality reduction and clustering algorithms ( k -means and Hierarchical Density-Based Spatial Clustering of Applications with Noise), we successfully segregate repeaters and nonrepeaters into distinct clusters, identifying over 100 potential repeater candidates. …”
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The development and psychometric properties of the persian linguistic inquiry and word count (P-LIWC): Emotions and cognitive processes categories by Mohammad Ali Soltani, Peyman MamSharifi, Reza Salehi Chegeni, Ali Safari, Soudabeh Ershadi Manesh, Hamidreza Keshavarz, Majid Afshari, MohamadSajad Ghafouri, Mojtaba Mohammadi, Fateme Tavakoli

“…Specifically, with the help of algorithms and computational processes, it can analyze elements such as emotions, cognitions, attitudes, vocabulary, language style and social communication in texts, and the lack of a Persian version was one of the most important reasons for conducting this research. …”
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HRMS-SCD:A High-Resolution Multi-Scene Satellite Imagery Dataset for Comprehensive Land-Cover Semantic Change Detection by P. Guo, P. Guo, S. Yang, H. Zhang, X. Huang, X. Ning, Y. Han, R. Zhang, M. Hao

“…We benchmark eight state-of-the-art SCD algorithms using this dataset, providing critical performance metrics that serve as valuable references for subsequent research. …”
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Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study by Yanfei Chen, Bing Wang, Yankai Shi, Wenhao Qi, Shihua Cao, Bingsheng Wang, Ruihan Xie, Jiani Yao, Xiajing Lou, Chaoqun Dong, Xiaohong Zhu, Danni He

“…The study utilised Random Forest and Extreme Gradient Boosting (XGBoost) algorithms alongside traditional logistic regression for modelling. …”
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Assessing the temporal transferability of machine learning models for predicting processing pea yield and quality using Sentinel-2 and ERA5-land data by Michele Croci, Manuele Ragazzi, Alessandro Grassi, Giorgio Impollonia, Stefano Amaducci

“…This study aims to rigorously quantify this temporal transferability gap for both pea yield and TR prediction. Four ML algorithms (RF, XGBoost, GPR, SVMr) were evaluated using Sentinel-2 and ERA5-Land data from 2018 to 2024 in northern Italy. …”
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Fluocinolone acetonide 0.2 µg/day intravitreal implant in non-infectious uveitis affecting the posterior segment: EU expert user panel consensus-based clinical recommendations by Uwe Pleyer, Carlos Pavesio, Elisabetta Miserocchi, Carsten Heinz, Helen Devonport, Víctor Llorenç, Tomás Burke, Vanda Nogueira, Laurent Kodjikian, Bahram Bodaghi

“…Results The Clinical-expert-panel provided specific recommendations focusing on clinical presentation (unilateral/bilateral) of the NIU-PS; systemic involvement of NIU-PS and the lens status. Treatment algorithms were developed; one that refers to the management of patients with NIU-PS in clinical practice and another that establishes the best clinical scenarios for the use of FAc implants, both as monotherapy and as adjuvant therapy. …”
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Comprehensive multi-omics integration uncovers mitochondrial gene signatures for prognosis and personalized therapy in lung adenocarcinoma by Wenjia Zhang, Lei Zhao, Tiansheng Zheng, Lihong Fan, Kai Wang, Guoshu Li

“…By leveraging an ensemble of machine learning algorithms, we developed an Artificial Intelligence-Derived Prognostic Signature (AIDPS) model based on mitochondrial-related genes and validated its prognostic accuracy across multiple independent datasets. …”
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Development of an Efficient and Generalized MTSCAM Model to Predict Liquid Chromatography Retention Times of Organic Compounds by Mengdie Fan, Chenhui Sang, Hua Li, Yue Wei, Bin Zhang, Yang Xing, Jing Zhang, Jie Yin, Wei An, Bing Shao

“…Recently, machine learning and artificial intelligence algorithms have been applied to retention time prediction, which show unparalleled advantages over traditional experimental methods. …”
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