Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

“…Materials and methods: Various AI models as well as algorithms, such as machine learning (ML) and deep learning (DL) algorithms, have shown good results in the detection of diseases like heart failure, atrial fibrillation, coronary artery disease, and valvular heart disease. …”
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Research on an orchard row centreline multipoint autonomous navigation method based on LiDAR by Chen Zhenyu, Dou Hanjie, Gao Yuanyuan, Zhai Changyuan, Wang Xiu, Zou Wei

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Current status and prospects of artificial intelligence in the diagnosis and treatment of bladder tumors by GAN Xiya, WEI Wei

“…In the future, strengthening the establishment of datasets, optimizing algorithms, and integrating AI with clinical practice is expected to further enhance the effectiveness of AI in the diagnosis and treatment of bladder tumors, ultimately providing better medical services for patients. …”
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A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology by Yanni Wang, Wisit Cheungpasitporn, Hatem Ali, Jianbo Qing, Charat Thongprayoon, Wisit Kaewput, Karim M. Soliman, Zhengxing Huang, Min Yang, Zhongheng Zhang

“…This framework promotes rigorous peer review and enhances the reproducibility, clinical relevance, and fairness of AI research in nephrology. Moreover, AI/ML studies must confront biases—data, selection, and algorithmic—that adversely affect model performance. …”
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CrySPAI: A New Crystal Structure Prediction Software Based on Artificial Intelligence by Zongguo Wang, Ziyi Chen, Yang Yuan, Yangang Wang

“…To optimize the process across these modules, a distributed framework is implemented to parallelize tasks, and an automated workflow has been integrated into CrySPAI for seamless execution. This paper reports the development and implementation of the AI-based CrySPAI Crystal Prediction Software tool and its unique features.…”
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Risk Management and Optimization of Artificial Intelligence in E-Commerce Personalization Systems by Ao Ting Liang

“…Through case studies, it explores how leading e-commerce platforms integrate AI to optimize consumer engagement. A risk analysis highlights the challenges posed by AI, including privacy breaches, biased recommendations, and the risk of over-personalization. …”
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C-privacy: A social relationship-driven image customization sharing method in cyber-physical networks by Dapeng Wu, Jian Liu, Yangliang Wan, Zhigang Yang, Ruyan Wang, Xinqi Lin

“…However, many images are shared without any privacy processing, exposing hidden privacy risks and making sensitive content easily accessible to Artificial Intelligence(AI) algorithms. Existing image sharing methods lack fine-grained image sharing policies and cannot protect user privacy. …”
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Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities by Marcin Dębowski, Joanna Kazimierowicz, Marcin Zieliński

“…This review provides a comprehensive overview of current approaches and technological advances in multi-sensor systems applied to photobioreactors, including flow cytometry, IR spectroscopy, RGB sensors, in situ microscopy, and software-based sensors. The integration of artificial intelligence (AI), the Internet of Things (IoT) and metaheuristic algorithms into monitoring systems is also discussed as a promising way to optimise key ecological, physicochemical, and biological parameters in real time. …”
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Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review by Mohammad Hossein Salemi, Elham Foroozandeh, Molouk Khademi Ashkzari

“…Future advancements include refining diagnostics through machine learning and natural language processing and integrating collaborative AI models for holistic, personalized care. …”
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Role of Artificial Intelligence in Dentistry by V. Hysenaj-Cakolli, B. Kolgeci, V. Hysenaj-Hoxha, D. Kolgeci

“…Future research should focus on enhancing AI algorithms, expanding training datasets, and integrating AI seamlessly into dental practice. …”
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The Future of Minimally Invasive GI and Capsule Diagnostics (REFLECT), October 2024 by Lea Østergaard Hansen, Alexandra Agache, Anastasios Koulaouzidis

“…Innovative technologies presented included robotics for drug delivery and magnetic endoscopic guidance systems. AI advancements were discussed for their potential to reduce diagnostic fatigue and standardize image interpretation, but ethical concerns and the need for transparent algorithms remain. …”
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Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…In the era of Industry 4.0 and the transition toward Industry 5.0, advanced manufacturing is increasingly driven by data analytics, artificial intelligence, and cyber-physical systems. The integration of intelligent monitoring systems and self-learning algorithms is reshaping machining processes, enabling higher efficiency, precision, and sustainability. …”
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An Enhanced Deep Neural Network Approach for WiFi Fingerprinting-Based Multi-Floor Indoor Localization by Shehu Lukman Ayinla, Azrina Abd Aziz, Micheal Drieberg, Misfa Susanto, Afidalina Tumian, Mazlaini Yahya

“…The CV process is repeated multiple times to assess the RFE’s generalization ability for optimal feature selection, and the BN algorithm is integrated into each layer of the DNN to ensure consistent activation value distribution and stabilization of the training process. …”
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WaveAttention-ResNet: a deep learning-based intelligent diagnostic model for the auxiliary diagnosis of multiple retinal diseases by Biao Guo, Daqing Wang, Ruiqi Zhang, Jia Hou, Wenchao Liu, YongFei Wu, Xudong Yang, Lijuan Zhang, Lijuan Zhang

“…ObjectiveThis study constructs a deep learning-based combined algorithm named WaveAttention ResNet (WARN) to investigate the classification accuracy for seven common retinal diseases and the feasibility of AI-assisted diagnosis in this field.MethodsFirst, a deep learning-based classification network is constructed. …”
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LSTM‐based real‐time stress detection using PPG signals on raspberry Pi by Amin Rostami, Koorosh Motaman, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…The authors have developed an advanced AI algorithm that achieves high accuracy in real‐time stress detection using photoplethysmography (PPG) sensors while significantly reducing computational demands. …”
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Neural network based active control of base isolated structure considering isolator nonlinearity by Nour Elhouda Ghanemi, Mahdi Abdeddaim, Abdelhafid Ounis, Michela Basili

“…Simultaneously, artificial intelligence (AI), particularly machine learning algorithms, has opened new frontiers in structural control.MethodsThis study proposes a novel AI-based approach for structures equipped with nonlinear base isolation and an ATMD. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
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Role of Artificial Intelligence in Validating Palatal Rugae Patterns for Individual Identification: A Systematic Review by Balajee Venkatesh, A Haripriya

“…Objectives: To evaluate AI’s accuracy in identifying individuals using palatal rugae patterns to determine the reliability of AI software when integrated with different software platforms and its implications in forensics. …”
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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions by Krishnashree Achuthan, Sasangan Ramanathan, Sethuraman Srinivas, Raghu Raman

“…The study also highlights key current and future areas of focus, including quantum machine learning, explainable AI, integrating humanized AI and deepfakes.…”
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Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews by Kristen Foley, Caitlan McLean, Reece De Zylva, Gregorius Asa, Jordana Maio, Samantha Batchelor, Gideon Dzando, Ahmad Dimassi

“…From this juncture, we discuss ethical implications of the uncritical use of AI tools during review of literature and delineate essential reflexive responsibilities for researchers who integrate AI tools into their methodology for qualitative literature review.…”
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