Adapting Classification Neural Network Architectures for Medical Image Segmentation Using Explainable AI by Arturs Nikulins, Edgars Edelmers, Kaspars Sudars, Inese Polaka

“…Despite their effectiveness, these networks face significant challenges, including the need for extensive annotated patient data, time-consuming manual segmentation processes and restricted data access due to privacy concerns. …”
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Depth-Based Intervention Detection in the Neonatal Intensive Care Unit Using Vision Transformers by Zein Hajj-Ali, Yasmina Souley Dosso, Kim Greenwood, JoAnn Harrold, James R. Green

“…An intervention detection method based solely on depth data was developed using a vision transformer (ViT) model utilizing real-world data from patients in the NICU. …”
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Adaptive Task Scheduling in Fog Computing Using Federated DQN and K-Means Clustering by Prashanth Choppara, S. Sudheer Mangalampalli

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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

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Securing and optimizing optical transmission in quantum wells using OAM and advanced modulation techniques by Muhammad Ahmad, Zhiping Wang, Ming Fang, Zhixiang Huang, Guoda Xie

“…However, current optical transmission methods encounter challenges in efficiently transmitting data due to limited OAM mode generation, reduced transmission privacy, and high atmospheric turbulence. …”
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A New Ultralightweight RFID Mutual Authentication Protocol: SASI Using Recursive Hash by Umar Mujahid, M. Najam-ul-Islam, Atif Raza Jafri, Qurat-ul-Ain, M. Ali Shami

“…Nonline of sight capability makes RFID systems much better choice than its contended systems (such as barcode, magnetic tape, etc.). Since the RFID uses wireless channel for communication with its associated devices, there should be some optimal encryption methods to secure the communicating data from adversaries. …”
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Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization by Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Ibrahim A. Fares, Abdelghani Dahou, Mansour Shrahili

“…The goal of the developed framework is to improve the detection of IDS without using centralized data to preserve privacy. Whereas it enhances the processing and detection capability of huge amounts of data generated from IoT devices. …”
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Decentralized federated learning using validation loss for model sharing in crop disease classification by Denis Mamba Kabala, Adel Hafiane, Laurent Bobelin, Raphaël Canals

“…Several AI methods have been employed for this purpose, but despite achieving good results, many challenges remain, such as protecting farmers’ data, using machine learning on edge devices, and employing collaborative learning. …”
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How to Write Effective Prompts for Screening Biomedical Literature Using Large Language Models by Maria Teresa Colangelo, Stefano Guizzardi, Marco Meleti, Elena Calciolari, Carlo Galli

“…Finally, we explore emerging trends, including multi-stage screening pipelines and fine-tuning, while noting ethical considerations related to data privacy and transparency. By applying systematic prompt engineering and rigorous evaluation, researchers can optimize LLM-based screening processes, allowing for faster and more comprehensive evidence synthesis across biomedical disciplines.…”
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Key challenges of launching national cryptocurrencies using extended FMEA under uncertainty environment by Zeynab Tghavi, Farid Ahmadi, Saeid Jafarzadeh Ghoushchi

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Scientific Evidence for Clinical Text Summarization Using Large Language Models: Scoping Review by Lydie Bednarczyk, Daniel Reichenpfader, Christophe Gaudet-Blavignac, Amon Kenna Ette, Jamil Zaghir, Yuanyuan Zheng, Adel Bensahla, Mina Bjelogrlic, Christian Lovis

“…ResultsA total of 30 original studies were included in the analysis. All used observational retrospective designs, mainly using real patient data (n=28, 93%). …”
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Performance Evaluation and Analysis of LightCert4IoT Using Cooja-Contiki Simulator by David Khoury, Samir Haddad, Patrick Sondi, Gaby Abou Haidar, David Semaan, Jinane Sayah

“…Scalability, resource limitations, and privacy concerns are analyzed as IoT devices handle sensitive information, and the transparent and immutable nature of blockchain can raise data protection. …”
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Secure and Reversible Face De-Identification With Format-Preserving Encryption by Heehwan Kim, Sungjune Park, Daeseon Choi

“…In conclusion, the proposed method provides a robust privacy-preserving solution for facial data in digital environments, balancing security and utility while supporting lawful restoration.…”
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A Hybrid Deep Learning Framework for Deepfake Detection Using Temporal and Spatial Features by Fazeel Zafar, Talha Ahmed Khan, Salas Akbar, Muhammad Talha Ubaid, Sameena Javaid, Kushsairy Abdul Kadir

“…The system dissects video inputs into frames to extract features comprehensively by using Multi Test Convolutional Networks (MTCNN). …”
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Global Health care Professionals’ Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study by Ecem Ozkan, Aysun Tekin, Mahmut Can Ozkan, Daniel Cabrera, Alexander Niven, Yue Dong

“…The majority of our participants found ChatGPT to be useful; however, there are concerns about patient privacy, data security, and its legal and ethical issues as well as the accuracy of its information. …”
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Ethical guidelines for journalistic use of GenAI. The main trends in the international debate and progress in self-regulation in Spain by Rosana Sanahuja-Sanahuja, Pablo López-Rabadán

“…To deal with this situation, academics and the journalistic sector have been publishing different professional guidelines and codes in an attempt to guide the ethical use of this technology. Based on the systematic review of three sets of academic guidelines and 18 important professional publications, and including data from more than 60 countries, this study establishes a double objective: to identify the main trends determining the international ethical debate; and to examine the degree of correspondence between these trends and the first self-regulation initiatives launched by the Spanish media. …”
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Knowledge, Attitudes, and Perceptions of Chronic Patients in Saudi Arabia Regarding the Use of Artificial Intelligence to Improve Medication Adherence by Alsanosi SM, Aldajani AQ, Gheliwi HA, Alotibi MM, Bokhari GS, Almatrafi OA, Alqawlaq AK, Abujamai JZ, Shaikhomer M, Alhindi YZ, Alshanberi AM

“…Safaa M Alsanosi,1 Asayel Q Aldajani,2 Hasnaa A Gheliwi,2 Manar M Alotibi,2 Ghadi S Bokhari,2 Orjuwan A Almatrafi,2 Abdulelah K Alqawlaq,3 Jakleen Z Abujamai,3 Mohammed Shaikhomer,4 Yosra Z Alhindi,1 Asim M Alshanberi3 1Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al Qura University, Makkah, Saudi Arabia; 2Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia; 3General Medicine Program, Batterjee Medical College, Jeddah, Saudi Arabia; 4Department of Internal Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi ArabiaCorrespondence: Safaa M Alsanosi, Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al Qura University, Makkah, Saudi Arabia, Email smsanosi@uqu.edu.saBackground: Artificial intelligence (AI) is advancing healthcare globally and in Saudi Arabia, enhancing patient care, diagnostics, and administrative efficiency, despite challenges such as data privacy and regulation. This study explores knowledge, attitudes, and perceptions (KAP) regarding AI in medication adherence among chronic patients in Makkah region, Saudi Arabia.Methods: A cross-sectional study was conducted among patients with chronic diseases in the Makkah region, Saudi Arabia, from 1 July to 31 December 2024. …”
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Prevalence of adolescent dual tobacco use and its associated factors: findings from a cross-sectional study by Mohd Firdaus Razali, Mohd Ruhaizie Riyadzi, Hamizatul Akmal Abd Hamid, Khaw Wan-Fei, Ummi Nadiah Yusoff

“…Objective To determine the prevalence and its associated factors of dual tobacco use among Malaysian adolescents in developing effective public health strategies.Design Cross-sectional study.Setting This study analysed data from the National Health and Morbidity Survey (NHMS) 2022: Adolescent Health Survey (AHS), a nationwide cross-sectional survey conducted among secondary school students across Malaysia.Participants This cross-sectional study used data from the NHMS 2022: AHS, which included a representative national sample of Malaysian adolescents between the ages of 13 and 17. …”
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Health Care Professionals’ Use of Digital Technology in the Secondary Prevention of Cardiovascular Disease in Austria: Online Survey Study by Luisa Lunz, Sabine Würth, Stefan Tino Kulnik

“…Quantitative survey data were analyzed using descriptive statistics, group comparison tests, and association statistics. …”
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CPS-IIoT-P2Attention: Explainable Privacy-Preserving With Scaled Dot-Product Attention in Cyber-Physical System-Industrial IoT Network by Yakub Kayode Saheed, Joshua Ebere Chukwuere

“…The findings revealed that the scaled dot product attention mechanism dramatically boosts model performance, while Pearson correlation and agglomerative clustering safeguard data privacy in CPS-IIoT, surpassing the performance of existing state-of-the-art (SOTA) models. …”
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