Integrating AI into Cancer Immunotherapy—A Narrative Review of Current Applications and Future Directions by David B. Olawade, Aanuoluwapo Clement David-Olawade, Temitope Adereni, Eghosasere Egbon, Jennifer Teke, Stergios Boussios

“…However, challenges related to data privacy, algorithm transparency, and clinical integration must be addressed. …”
Get full text

Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring by Fang Li, Shengguo Wang, Zhi Gao, Maofeng Qing, Shan Pan, Yingying Liu, Chengchen Hu

“…However, ethical challenges, including data privacy concerns and algorithmic biases, must be addressed to ensure fair and effective implementation. …”
Get full text

A Framework for Privacy-Preserving in IoV Using Federated Learning With Differential Privacy by Muhammad Adnan, Madiha Haider Syed, Adeel Anjum, Semeen Rehman

“…We proposed a computationally efficient group leader selection process based on centeredness, rule obeyed, and OBU resources, reducing overhead by 20%, integrating FL with DP to preserve data privacy without sacrificing utility, and achieving a 15% improvement in location accuracy under privacy constraints, validating the scalability and robustness of the framework through extensive simulations involving up to 300 vehicles. …”
Get full text

Evaluation of EGFR-TKIs and ICIs treatment stratification in non-small cell lung cancer using an encrypted multidimensional radiomics approach by Xingping Zhang, Xingting Qiu, Yue Zhang, Qingwen Lai, Yanchun Zhang, Guijuan Zhang

“…Abstract Background Radiomics holds great potential for the noninvasive evaluation of EGFR-TKIs and ICIs responses, but data privacy and model robustness challenges limit its current efficacy and safety. …”
Get full text

Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…Securing data transactions across computer networks presents significant challenges, particularly concerning data privacy and cybersecurity threats. These issues are particularly critical in electric vehicle charging stations (EVCSs) due to the sensitive data involved, such as data breaches, unauthorized access, and privacy concerns. …”
Get full text

Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework by Arvind R. Singh, R. Seshu Kumar, K. Reddy Madhavi, Faisal Alsaif, Mohit Bajaj, Ievgen Zaitsev

“…Abstract The integration of Electric Vehicles (EVs) into power grids introduces several critical challenges, such as limited scalability, inefficiencies in real-time demand management, and significant data privacy and security vulnerabilities within centralized architectures. …”
Get full text

Balancing Privacy and Utility in Split Learning: An Adversarial Channel Pruning-Based Approach by Afnan Alhindi, Saad Al-Ahmadi, Mohamed Maher Ben Ismail

“…Accordingly, the proposed approach enhances data privacy without ceding the model’s performance in achieving the intended utility task. …”
Get full text

Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images by Chhaya Gupta, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

“…A new homomorphic encryption and decryption algorithm is also proposed to retain data privacy. A novel pruned YOLOv6 model with FedL is introduced in this study to differentiate benign and malignant tissues. …”
Get full text

Pengaruh E-Payment Trust terhadap Minat Transaksi pada E-Marketplace Menggunakan Framework Technology Acceptance Model (TAM) 3 by Merryana Lestari, Hindriyanto Dwi Purnomo, Irwan Sembiring

“…Often users have their own concerns in making payment transactions using e-Payment, one of the most basic concerns is about guaranteeing data security integrity and customer data privacy. User trust is seen as a big risk that can have an influence on buying interest in the e-Marketplace. …”
Get full text

Artificial intelligence on the agro-industry in the United States of America by Jahanara Akter, Sadia Islam Nilima, Rakibul Hasan, Anamika Tiwari, Md Wali Ullah, Md Kamruzzaman

“…It scrutinized the emergence of robot farmers and AI's role in reshaping farming practices while acknowledging the inherent problems associated with AI implementation, including accessibility, data privacy, and potential job displacement. Moreover, the study explored how AI tools can catalyze the development of agribusiness, offering insights into overcoming existing challenges through innovative solutions. …”
Get full text

Advancing privacy-aware machine learning on sensitive data via edge-based continual µ-training for personalized large models by Zhaojing Huang, Leping Yu, Luis Fernando Herbozo Contreras, Kamran Eshraghian, Nhan Duy Truong, Armin Nikpour, Omid Kavehei

“…This study establishes a foundational framework for advancing personalized model adaptation, on-device inference and fine-tuning while emphasizing the importance of safeguarding data privacy in model development.…”
Get full text

VP-SFDA: Visual Prompt Source-Free Domain Adaptation for Cross-Modal Medical Image by Yixin Chen, Yan Wang, Zhaoheng Xie

“…Background: Source-free unsupervised domain adaptation (SFUDA) methods aim to address the challenge of domain shift while preserving data privacy. Existing SFUDA approaches construct reliable and confident pseudo-labels for target-domain data through denoising methods, thereby guiding the training of the target-domain model. …”
Get full text

Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Federated Learning (FL) offers an encouraging solution to address these challenges by providing a privacy-preserving solution for investigating and detecting cyberattacks in IoT systems without negotiating data privacy. Nevertheless, the possibility of FL regarding IoT forensics remains mostly unexplored. …”
Get full text

Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things by A. Sasikumar, Logesh Ravi, Malathi Devarajan, A. Selvalakshmi, Abdulaziz Turki Almaktoom, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…The analyses and experimental findings show that the proposed blockchain-integrated edge computing architecture is better than the existing schemes in terms of data sharing, data privacy, and security.…”
Get full text

Gemelos digitales pulmonares by Ana Fernández-Tena, Carlos Arnedo, Guillaume Houzeaux, Beatriz Eguzkitza

“…Despite advances, the implementation of DTs in clinical practice faces challenges related to data integration, computational efficiency, and ethical considerations regarding data privacy. Nevertheless, lung DTs offer clear promise for improving precision medicine, optimizing patient care, and improving clinical outcomes.…”
Get full text

Enhancing antimicrobial resistance strategies: Leveraging artificial intelligence for improved outcomes by Aeshah M. Mohammed, Mohammed Mohammed, Jawad K. Oleiwi, Azlin F. Osman, Tijjani Adam, Bashir O. Betar, Subash C.B. Gopinath, Falah H. Ihmedee

“…Despite facing challenges such as data privacy concerns and the need for robust regulatory frameworks, AI holds promise for significantly improving AMR outcomes. …”
Get full text

Workflow for Conflict and Reinforcement Identification Based on STPA and STRIDE by Andrei Carniel, Juliana de Melo Bezerra, Celso Massaki Hirata

“…First, requirements identification is generally made using methods of specific concern, e.g. safety, cybersecurity, data privacy, and business, and it does not consider concerns jointly. …”
Get full text

Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security by Mateo Mejia-Herrera, Juan Botero-Valencia, José Ortega, Ruber Hernández-García

“…The perimeter alert system offers numerous advantages, including edge processing for enhanced data privacy and reduced latency, integrating multiple sensors for increased accuracy, and a decentralized approach to improving security. …”
Get full text

The Efficacy of Conversational AI in Rectifying the Theory-of-Mind and Autonomy Biases: Comparative Analysis by Marcin Rządeczka, Anna Sterna, Julia Stolińska, Paulina Kaczyńska, Marcin Moskalewicz

“…Future research should focus on enhancing affective response mechanisms and addressing ethical concerns such as bias mitigation and data privacy to ensure safe, effective AI-based mental health support.…”
Get full text

Bibliometric analysis of research in ethical concerns and dilemmas of digital mental health care in the last two decades by Poonam Sharma, Rekha Wagani, Mahima Anna Varghese

“…Analyses reflects that the top cited articles on Digital Mental healthcare are specifically directed on bringing out some of the key concerns of data privacy, emergency response, therapist competency and consent which requires appropriate handling Otherwise they may be cause of distress to client and question the trustworthiness of the Digital Mental Health Care system.ConclusionThe concerns brought out through this bibliometric analysis could be important guiding principles for online mental health services. …”
Get full text