A Survey of Dental Caries Segmentation and Detection Techniques by Vincent Majanga, Serestina Viriri

“…Several methods have been introduced to improve the quality of images for faster caries detection. …”
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Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation by Jerry J. Lou, Peter Chang, Kiana D. Nava, Chanon Chantaduly, Hsin-Pei Wang, William H. Yong, Viharkumar Patel, Ajinkya J. Chaudhari, La Rissa Vasquez, Edwin Monuki, Elizabeth Head, Harry V. Vinters, Shino Magaki, Danielle J. Harvey, Chen-Nee Chuah, Charles S. DeCarli, Christopher K. Williams, Michael Keiser, Brittany N. Dugger

“…ArtSeg comprises three ML models for blood vessel detection, arteriolosclerosis classification, and segmentation of arteriolosclerotic vessel walls and lumens. …”
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Optimizing Small Cell Performance: A New MIMO Paradigm With Distributed ASTAR-RISs by Shakil Ahmed, Ahmed E. Kamal, Mohamed Y. Selim, Md Akbar Hossain, Saifur Rahman Sabuj

“…Unlike conventional RIS, ASTAR-RISs actively amplify and transmit signals, effectively mitigating the limited propagation challenge and improving signal strength, especially in dense ScNs. …”
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Advanced Deep Learning and Machine Learning Techniques for MRI Brain Tumor Analysis: A Review by Rim Missaoui, Wided Hechkel, Wajdi Saadaoui, Abdelhamid Helali, Marco Leo

“…In this study, we focus on current advances in medical imaging, particularly magnetic resonance imaging (MRI), and how machine learning (ML) and deep learning (DL) algorithms might be combined with clinical assessments to improve brain tumor diagnosis. …”
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Criteria for predicting the initiation of rolling contact fatigue damage in the railway wheels and rails by V. I. Sakalo, A. V. Sakalo

“…The assumptions that are used in the development of the algorithms concerning the models of the contacting bodies, the shape of the contact patch, the distribution of the contact pressures and the tangential forces are considered. …”
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Verifying the Effects of the Grey Level Co-Occurrence Matrix and Topographic–Hydrologic Features on Automatic Gully Extraction in Dexiang Town, Bayan County, China by Zhuo Chen, Tao Liu

“…The results show that the validated gully <i>IOU</i> was 0.4299 (±0.0082) when only the red (R), green (G), blue (B), and near-infrared (NIR) bands were applied, and solely combining the topographic–hydrologic features with the RGB and NIR bands significantly improved the performance of the models, which boosted the validated gully <i>IOU</i> to 0.4796 (±0.0146). …”
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A Fuzzy Based Sensor Web for Adaptive Prediction Framework to Enhance the Availability of Web Service by Sundharam Ramalingam, Lakshmi Mohandas

“…Thus, our framework significantly improves the availability of web services with minimal intervention from system administrators.…”
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Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription by Manaf Zargoush, Somayeh Ghazalbash, Mahsa Madani Hosseini, Farrokh Alemi, Dan Perri

“…Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. …”
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Issues of Designing Effective Educational Programs in the Field of “Applied Informatics” in the Conditions of Innovative Development by Yu. F. Telnov, M. S. Gasparian, M. A. Filyuk

“…As a result of the analysis of the factors for improving the quality of the educational process, the ways to improve training of bachelors in the field of “Applied Informatics” in the context of combining ontologies of professional and educational standards are outlined. …”
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Artificial Intelligence in Revolutionizing Kidney Care and Beyond: Kid-AI Revolution by Kounaina Khan, Farhan Zameer, Pratheek Jain, Ravi KR, Vidya Niranjan, Manoj S, Ravish H, Subrahmanya Padyana

“…Despite the transformative potential, the review acknowledges challenges such as data privacy, interpretability of AI models, the imperative need for trust in AI-driven recommendations for broad applicability, external validation, and improved clinical decision-making. …”
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CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…ObjectiveThis research aims to comprehensively investigate the operational dynamics of a 10t/d sludge and biomass co-incineration fluidized bed reactor through Computational Particle Fluid Dynamics (CPFD) modeling, addressing critical gaps in industrial-scale waste valorization. …”
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First In-Orbit Validation of Interferometric GNSS-R Altimetry: Mission Overview and Initial Results by Yixuan Sun, Yueqiang Sun, Junming Xia, Lingyong Huang, Qifei Du, Weihua Bai, Xianyi Wang, Dongwei Wang, Yuerong Cai, Lichang Duan, Zhenhe Zhai, Bin Guan, Zhiyong Huang, Shizhong Li, Feixiong Huang, Cong Yin, Rui Liu

“…We developed a refined DM waveform-matching algorithm that precisely extracts the propagation delays between reflected and direct GNSS signals, enabling the retrieval of global sea surface height (SSH) through the interferometric altimetry model. …”
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Towards consistently measuring and monitoring habitat condition with airborne laser scanning and unmanned aerial vehicles by W. Daniel Kissling, Yifang Shi, Jinhu Wang, Agata Walicka, Charles George, Jesper E. Moeslund, France Gerard

“…We suggest that a collaborative cloud virtual research environment (VRE) for habitat condition research and monitoring could provide solutions, including tools for data discovery, access, and data standardization, as well as geospatial processing workflows for airborne LiDAR and UAV data. A VRE would also improve data management, metadata standardization, workflow reproducibility, and transferability of structure-from-motion algorithms and machine learning models such as random forests and convolutional neural networks. …”
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Functional Connectivity Metrics in Temporal Lobe Epilepsy: A Machine Learning Perspective With MEG by M. V. Suhas, N. Mariyappa, A. Karunakar Kotegar, M. Ravindranadh Chowdary, K. Raghavendra, Ajay Asranna, L. G. Viswanathan, H. Anitha, Sanjib Sinha

“…Overall, this study underscores the potential of MEG and functional connectivity analysis using specific frequency bands and machine learning models for classifying TLE and HC with high accuracy, which may contribute to improved diagnosis and management of epilepsy.…”
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Data source and utilization of artificial intelligence technologies in vascular surgery—a scoping review by Katarzyna Powezka, Katarzyna Powezka, Katarzyna Powezka, Karin Slater, David Brind, Michael Wall, Michael Wall, Georgios Gkoutos, Maciej Juszczak, Maciej Juszczak

“…This can be used to develop more accurate risk prediction models, support shared-decision model, and identify patients for trials to improve recruitment.ConclusionUtilisation of different data sources and AI technologies depends on the purpose of the undertaken research. …”
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The effect of Pressurised Intraperitoneal Aerosol Chemotherapy on the quality of life of patients with primary diagnosed ovarian cancer with peritoneal carcinomatosis during combin... by A. S. Dzasokhov, A. A. Kostin, V. L. Astashov, A. V. Turiev, A. D. Uskov

“…In the main group, the basic level of assessment of the quality of life was 53.8 ± 11.3 points. Subsequently, an improvement in the indicators was also revealed: 49.6 ± 7.5 points, 44.2 ± 5.3 points and 42.1 ± 5.4 points, respectively. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
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Reverberation Mapping of Lamppost and Wind Structures in Accretion Thin Disks by James Hung-Hsu Chan, Joshua Fagin, Henry Best, Matthew J. O’Dowd

“…The strong degeneracy between the temperature slope and accretion rate suggests that incorporating flux spectra or spectral energy distributions could improve fitting accuracy. Our simulation approach rapidly generates quasar light curves while accommodating various observational scenarios for reverberation mapping, making it well-suited for training machine learning algorithms.…”
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Advanced Interpretation of Bullet-Affected Chest X-Rays Using Deep Transfer Learning by Shaheer Khan, Nirban Bhowmick, Azib Farooq, Muhammad Zahid, Sultan Shoaib, Saqlain Razzaq, Abdul Razzaq, Yasar Amin

“…Special deep learning algorithms went through a process of optimization before researchers improved their ability to detect and place objects. …”
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INCOIS air-sea Flux Reference System onboard ORV Sagar Nidhi: overview and initial results by B. Praveen Kumar, Abhijith Raj, Abhijith Raj, Asish K. Sasidharan, Asish K. Sasidharan, N. Sureshkumar, A. A. Gnanaraj, Deepak Sankar, K. Ramasundaram, Venkata Jampana, E. Pattabhi Rama Rao

“…Data from this system are useful for validating model outputs and satellite observations, refining flux parameterizations, marine boundary layer studies, and improving air-sea interaction models. …”
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