Ethical Dilemmas in the Clinical Application of Medical Artificial Intelligence: From Information Systems to Robotics by Lanying WANG, Rui ZHENG, Xianwei LIU

“…It explores core issues such as privacy leakage caused by data triangulation, distribution of data value, prejudice against rare diseases and vulnerable groups, challenges of medical AI to the role of doctors and reshaping of the doctor-patient relationship, unclear individual benefits of patients, and unclear attribution of responsibilities. …”
Get full text

Artificial Intelligence in Healthcare Applications Challenges and Opportunities for Improved Patient Outcomes by Rashid Zahraa M., Balaram Allam, Lavanya Chinthamalla, Mary P Shyamala Anto, Tiwari Mohit, P K Chidambaram

“…Cohorts combined with longitudinal case studies advance the study; ethical perspectives, data quality improvement, and bias mitigation emphasises justification for the validity and generalizability of the AI technologies used, which improves the quality of the study. …”
Get full text

A Survey on Immersive Cyber Situational Awareness Systems by Hussain Ahmad, Faheem Ullah, Rehan Jafri

Get full text

Cybersecurity Framework: Addressing Resiliency in Welsh SMEs for Digital Transformation and Industry 5.0 by Nisha Rawindaran, Ambikesh Jayal, Edmond Prakash

Get full text

Inferring TLB Configuration with Performance Tools by Cristian Agredo, Tor J. Langehaug, Scott R. Graham

Get full text

Suspicious Financial Activity in the Context of In-Game Asset Exchange Marketplace by Emil Eminov, Stephen V. Flowerday

Get full text

A Secure and Scalable Authentication and Communication Protocol for Smart Grids by Muhammad Asfand Hafeez, Kazi Hassan Shakib, Arslan Munir

Get full text

Enhanced Deep Autoencoder-Based Reinforcement Learning Model with Improved Flamingo Search Policy Selection for Attack Classification by Dharani Kanta Roy, Hemanta Kumar Kalita

Get full text

La tutela dei dati biometrici tra GDPR e AI ACT by Anna Carla Nazzaro

“…It examines the definition of biometric data and its use for identification, authentication, and categorization, with a focus on the risks of discrimination and misuse. …”
Get full text

A multicenter bladder cancer MRI dataset and baseline evaluation of federated learning in clinical application by Kangyang Cao, Yujian Zou, Chang Zhang, Weijing Zhang, Jie Zhang, Guojie Wang, Chu Zhang, Jiegeng Lyu, Yue Sun, Hongyuan Zhang, Bin Huang, Lei Deng, Shuiqing Yang, Jianpeng Li, Bingsheng Huang

“…Nevertheless, it has been observed that certain investigations use data from various medical facilities to train models for BCa, which may pose a privacy risk. …”
Get full text

Digital bioethics... Next step forward? by Giuseppe Corasaniti

Get full text

A dataset to train intrusion detection systems based on machine learning models for electrical substationsZenodo by Esteban Damián Gutiérrez Mlot, Jose Saldana, Ricardo J. Rodríguez, Igor Kotsiuba, Carlos Gañán

“…The dataset includes raw network captures and flows from real substations, filtered and anonymized to ensure privacy. It covers the main protocols and standards used in substation environments: IEC61850, IEC104, NTP, and PTP. …”
Get full text

Kenyan sign language word-based pose datasetZenodo by Ezekiel Maina, Lilian Wanzare, James Obuhuma, Mildred Ayere, Maurine Kang'ahi, Joel Okutoyi

“…The dataset includes 20,000 video recordings of KSL gestures, converted into anonymized stickman representations alongside detailed 3D pose coordinates stored in .npy files. The data collection process focused on preserving participant privacy while ensuring the integrity of gesture data. …”
Get full text

A Comprehensive Polish Medical Speech Dataset for Enhancing Automatic Medical Dictation by Andrzej Czyżewski, Sebastian Cygert, Karolina Marciniuk, Maciej Szczodrak, Arkadiusz Harasimiuk, Piotr Odya, Marina Galanina, Piotr Szczuko, Bożena Kostek, Beata Graff, Dariusz Szplit, Mariusz Budzisz, Krzysztof Narkiewicz

“…Additionally, we release two enhanced versions: one anonymized for privacy-sensitive use and another synthetic version created via text-to-speech, totaling over 83 hours and nearly 50,000 samples. …”
Get full text

An open-source and spatially diverse synthetic population dataset for agent-based modelling and microsimulation in IrelandZenodo/GitHub by Seán Caulfield Curley, Karl Mason, Patrick Mannion

“…However, individual-level data is not available for the vast majority of populations, Ireland included, due to privacy concerns. …”
Get full text

Street-level imagery dataset for the detection of informal vendors in urban environmentZenodo by Keyla Garcia-Jaimes, John R. Ballesteros, John W. Branch-Bedoya

“…The original dataset contains 1397 images, with an average size of 5 MB per image, resulting in a total dataset size of 4.63 GB. Privacy compliance with GDPR guidelines was achieved by anonymizing pedestrian faces and vehicle license plates using an open-source YOLO object detection pipeline. …”
Get full text

AutoFactory Dataset to Support AI in Manufacturing SystemsHugging Face by Abderrahmane Boudribila, Abdelouahed Tajer, Zakaria Boulghasoul

“…It runs locally to preserve data privacy and provides a user-friendly interface. …”
Get full text

Unsupervised feature selection and class labeling for credit card fraud by Robert K. L. Kennedy, Flavio Villanustre, Taghi M. Khoshgoftaar

“…In this paper, we present a fully unsupervised approach that combines SHapley Additive exPlanations (SHAP) for feature selection with an autoencoder based method for generating class labels for a widely used credit card fraud detection dataset. Using this publicly available and well-known dataset, we construct different sized datasets using feature selection, generate class labels, and measure the quality and efficacy of the labels. …”
Get full text

Enhancing Byzantine robustness of federated learning via tripartite adaptive authentication by Xiaomeng Li, Yanjun Li, Hui Wan, Cong Wang

Get full text

OCT-SelfNet: a self-supervised framework with multi-source datasets for generalized retinal disease detection by Fatema-E Jannat, Sina Gholami, Minhaj Nur Alam, Hamed Tabkhi

“…This is mainly due to the limited availability of labeled medical image data, driven by privacy concerns. To address this, we have developed a self-supervised machine learning framework for detecting eye diseases from optical coherence tomography (OCT) images, aiming to achieve generalized learning while minimizing the need for large labeled datasets.MethodsOur framework, OCT-SelfNet, effectively addresses the challenge of data scarcity by integrating diverse datasets from multiple sources, ensuring a comprehensive representation of eye diseases. …”
Get full text