Steganography in IoT: A Comprehensive Survey on Approaches, Challenges, and Future Directions by Maha Driss, Lamia Berriche, Safa Ben Atitallah, Siwar Rekik

“…Steganography is an intriguing approach that allows hiding sensitive information within seemingly ordinary data, preventing unauthorized parties from detecting and accessing it. Existing studies on IoT security lack a comprehensive analysis of steganographic techniques tailored for IoT-specific constraints. …”
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Implications of artificial intelligence in periodontal treatment maintenance: a scoping review by Raafat Musief Sarakbi, Sudhir Rama Varma, Sudhir Rama Varma, Lovely Muthiah Annamma, Vinay Sivaswamy, Vinay Sivaswamy

“…AI demonstrated superior performance in detecting periodontal conditions, with accuracy rates surpassing 90% in some studies. …”
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Non-Contact Platform for the Assessment of Physical Function in Older Adults: A Pilot Study by Ana Sobrino-Santos, Pedro Anuarbe, Carlos Fernandez-Viadero, Roberto García-García, José Miguel López-Higuera, Luis Rodríguez-Cobo, Adolfo Cobo

“…By applying markerless motion capture algorithms, the system provides key biomechanical parameters such as center of mass displacement, knee angles, and sway trajectories. …”
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Prediction of bladder cancer prognosis and immune microenvironment assessment using machine learning and deep learning models by Weihao Nie, Yiheng Jiang, Luhan Yao, Xinqing Zhu, Abdullah Y. AL-Danakh, Wenlong Liu, Qiwei Chen, Deyong Yang

“…In this study, we integrated 10 machine learning algorithms to develop an immune-related machine learning signature (IRMLS) and subsequently created a deep learning model to detect the IRMLS subtype based on pathological images. …”
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Cathepsin C correlates with M2 macrophage infiltration and regulates the tumor growth and metastasis in non-small cell lung cancer by Xiaoxia Tong, Ting Zhu, Li Ma, Xiaohu Yang, Chenghui Li, Yibing Liu, Xuan Qin, Yanguang Ding, Hongwei Xia, Yonglei Liu

“…Then, CTSC, CD68, CD163 expression levels were detected by immunohistochemistry in our clinical NSCLC cohort. …”
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Recent Advances in Flexible and Wearable Gas Sensors Harnessing the Potential of 2D Materials by Azmira Jannat, Md Mehdi Masud Talukder, Zhong Li, Jian Zhen Ou

“…In the Internet of Things era, flexible and wearable gas sensors are increasingly vital for real‐time monitoring in healthcare, environmental safety, and industrial security. These sensors detect hazardous gases at room temperature and seamlessly integrate with clothing and portable devices. …”
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Boerhaave Syndrome - A Rare but Serious Esophageal Emergency by Paula Szarek, Jakub Kołacz, Patrycja Oleś, Marcin Kwiatkowski, Paulina Bochniak

“…Aim of the Study: This review aims to provide a comprehensive overview of the syndrome’s definition, pathophysiology, clinical characteristics, diagnostic algorithms, and current therapeutic strategies, emphasizing the pivotal role of early intervention in reducing morbidity and mortality. …”
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Machine learning based adaptive traffic prediction and control using edge impulse platform by Manoj Tolani, G. E. Saathwik, Ayush Roy, L. A. Ameeth, Dhanush Bharadwaj Rao, Ambar Bajpai, Arun Balodi

“…Using machine learning algorithms, the system can forecast future traffic conditions and optimize real-time traffic control by significantly reducing congestion and delays. …”
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Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images by Mahsa Raisi-Nafchi, Mahnoosh Tajmirriahi, Hossein Rabbani, Zahra Amini

“…Three classification algorithms were evaluated: support vector machine, K-nearest neighbor, and random forest. …”
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Artificial Intelligence: The Strategy of Financial Risk Management by A. Kumar, A Kumar, S. Kumari, S. Kumar, N. Kumari, A. K. Behura

“…AI helps to monitor the quality of information received, detect fraud and search for the right information on the Internet. …”
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Explainable AI Methods for Underwater Mine Warfare by Guy Junior Richard, Jerome Habonneau, Didier Gueriot, Jean-Marc Le Caillec

“…Artificial intelligence (AI) has brought new algorithms providing high performance compared to the usual methods. …”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…The spectral data sets were analyzed using decision tree and support vector machine (SVM) algorithms to identify the most accurate model for distinguishing diseased and healthy plants. …”
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Combining first principles and machine learning for rapid assessment response of WO3 based gas sensors by Ran Zhang, Guo Chen, Shasha Gao, Lu Chen, Yongchao Cheng, Xiuquan Gu, Yue Wang

“…The rapid advancement of gas sensitive properties in metal oxides is crucial for detecting hazardous gases in industrial and coal mining environments. …”
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Intelligent Manufacturing in Wine Barrel Production: Deep Learning-Based Wood Stave Classification by Frank A. Ricardo, Martxel Eizaguirre, Desmond K. Moru, Diego Borro

“…Several techniques using classical image processing and deep learning have been developed to detect tree-ring boundaries, but they often struggle with woods exhibiting heterogeneity and texture irregularities. (2) Methods: This study proposes a hybrid approach combining classical computer vision techniques for preprocessing with deep learning algorithms for classification, designed for continuous automated processing. …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. …”
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Optimized deep learning models for stress-based stroke prediction from EEG signals by Sivasankaran Pichandi, Gomathy Balasubramanian, Venkatesh Chakrapani, J. Samuel Manoharan

“…Abstract In this research, the use of non-invasive electrode-based EEG (electroencephalogram) signal measurement as a means to detect emotional and stress-related factors in individuals, is explored. …”
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Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson’s Disease: A Systematic Review and Meta-Analysis by Feng Zhang, Liangqing Guo, Lin Liu, Xiaochun Han

“…We systematically searched for studies that applied machine learning algorithms to MRI data for diagnosing PD with mild cognitive impairment (PD-MCI). …”
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High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
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Design for Testability of Integrated Circuits and Project Protection Difficulties by E. Ph. Pevtsov, T. A. Demenkova, A. A. Shnyakin

“…It was proposed, inter alia: 1) to analyze the libraries of standard elements used in the project with full disclosure of their specifications; 2) to create nodes with the physical non-cloning function in the projects on the basis of the libraries of standard elements in models and analysis programs; 3) to analyze IP modules used in the project with the maximum disclosure of structure, methods and algorithms for providing test coverings; 4) to provide for the development in projects of special test kits and methods of their generation at the design stage of functions in order to detect malicious nodes and programs both within SoC cores and at the level of system buses; 5) to develop at the design stage and to apply during tests a technique of special hardware measurements of parameters of the manufactured circuits and analysis of their results, inter alia, according to measurements of delays in distribution of signals and/or buses current consumption.…”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Our tool allows users to analyze the collective behavior of features in each pro-group (biological groups) utilizing ML algorithms. In addition, by constructing the pro-groups and equalizing the feature numbers in each pro-group using the FIS component, this process achieves a significant 20% speedup over the 3Mint tool. …”
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