Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

“…By using deep learning models and advanced algorithms, AI can identify patterns and relationships in complex data, thereby providing deeper insights for better decision making. …”
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DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection by Shijin Song, Sen Du, Yuefeng Song, Yongxin Zhu

“…However, existing pruning algorithms exhibit high sensitivity to network architectures and typically require multiple sessions of retraining to identify optimal structures. …”
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Research and application of mining AI video edge computing technology by ZHANG Liya, HAO Bonan, MA Zheng, YANG Zhifang

“…A lightweight software development kit (SDK) framework based on the register machine was proposed to decouple operators, improving the parallel computing ability of the algorithms and reducing the storage requirements of the SDK. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

“…<b>Conclusions</b>: By integrating ML with EEG analysis, this study highlights the potential for future healthcare applications, including neurorehabilitation, anxiety disorder therapy, and predictive clinical models. Future research should focus on optimizing ML algorithms, enhancing personalization, and addressing ethical concerns related to patient privacy.…”
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Churn prediction for SaaS company with machine learning by Hugo Eduardo Sanches, Ayslan Trevizan Possebom, Linnyer Beatrys Ruiz Aylon

“…Design/methodology/approach – Through a preprocessing and normalization of data, seven machine learning algorithms were applied. The models were trained, and also cross-validation and parameter tuning techniques were applied to improve results. …”
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A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning by Aleksander Radovan, Leo Mršić, Goran Đambić, Branko Mihaljević

“…The accurate counting of passengers in public transport systems is crucial for optimizing operations, improving service quality, and planning infrastructure. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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Human-machine co-adaptation to automated insulin delivery: a randomised clinical trial using digital twin technology by Boris P. Kovatchev, Patricio Colmegna, Jacopo Pavan, Jenny L. Diaz Castañeda, Maria F. Villa-Tamayo, Chaitanya L. K. Koravi, Giulio Santini, Carlene Alix, Meaghan Stumpf, Sue A. Brown

“…Abstract Most automated insulin delivery (AID) algorithms do not adapt to the changing physiology of their users, and none provide interactive means for user adaptation to the actions of AID. …”
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Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields by Ala Guennich, Mohamed Othmani, Hela Ltifi

“…The use of high-precision automatic algorithms for segmenting brain tumors has the potential to improve disease diagnosis, treatment monitoring, and large-scale pathological studies. …”
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Enhancing Visual Perception in Immersive VR and AR Environments: AI-Driven Color and Clarity Adjustments Under Dynamic Lighting Conditions by Maryam Abbasi, Paulo Váz, José Silva, Pedro Martins

“…Future work will focus on extending the model’s capability to handle more complex lighting scenarios.…”
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AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. …”
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Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours by Haoran Wang, Peter T. Brown, Jessica Ullom, Douglas P. Shepherd, Rainer Heintzmann, Benedict Diederich

“…To optimize DMD diffraction, we developed a model for tilt and roll pixel configurations, enabling use with various low-cost projectors in SIM setups. …”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…First, the EMRF module is employed to further enhance the model’s feature representation capability. Second, the EFPN optimizes cross-level information exchange and improves multi-scale data integration. …”
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Zero-Shot Learning for Accurate Project Duration Prediction in Crowdsourcing Software Development by Tahir Rashid, Inam Illahi, Qasim Umer, Muhammad Arfan Jaffar, Waheed Yousuf Ramay, Hanadi Hakami

“…The implementation of the proposed automated duration prediction model is crucial for enhancing the success rate of crowdsourcing projects, optimizing resource allocation, managing budgets effectively, and improving stakeholder satisfaction.…”
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RuleKit2: Faster and simpler rule learning by Adam Gudyś, Cezary Maszczyk, Joanna Badura, Adam Grzelak, Marek Sikora, Łukasz Wróbel

“…Here we present its second version. New algorithms and optimized implementations of those previously included, significantly improved the computational performance of our suite, reducing the analysis time of some data sets by two orders of magnitude. …”
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Obstacle avoidance and formation control of multiple unmanned vehicles in complex environments based on artificial potential field method by Yilin MEI, Likun CUI, Xueyan HU, Guangqi HU, Hao WANG

“…Specifically, the success rate of obstacle avoidance in dynamic environments increased by 35% compared to traditional algorithms and by 10% compared to improved algorithms. …”
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Non-operative management of locally advanced rectal cancer with an emphasis on outcomes and quality of life: a narrative review by In Ja Park

“…Total neoadjuvant therapy increases cCR rates to 30%–60% and expands the pool of WW candidates, but also intensifies the need for standardized response definitions and surveillance algorithms. WW offers organ preservation and quality‑of‑life improvements without compromising survival in carefully selected patients, provided that multidisciplinary teams ensure rigorous response assessment and lifelong monitoring. …”
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Disseminated intravascular coagulation by Satoshi Gando, Marcel Levi, Cheng-Hock Toh

“…Anticoagulant use has been extensively debated; however, the selection of optimal target patients could optimize their application and improve patient outcomes in the near future. …”
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Advancing Mental Health Care: Intelligent Assessments and Automated Generation of Personalized Advice via M.I.N.I and RoBERTa by Yuezhong Wu, Huan Xie, Lin Gu, Rongrong Chen, Shanshan Chen, Fanglan Wang, Yiwen Liu, Lingjiao Chen, Jinsong Tang

“…This paper integrates finite state machines, retrieval algorithms, semantic-matching models, and medical-knowledge graphs to design an innovative intelligent auxiliary evaluation tool and a personalized medical-advice generation application, aiming to improve the efficiency of mental health assessments and the provision of personalized medical advice. …”
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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…Through extensive experimentation across multiple datasets, our results demonstrate that BERT-based models consistently achieve superior performance, significantly improving detection accuracy in complex misinformation scenarios. …”
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