Check computer science papers: citations, claims and retractions

Preference Dynamics Under Personalized Recommendations

Dean, S., & Morgenstern, J. (2022) · Proceedings of the 23rd ACM Conference on Economics and Computation

Recommender Systems and TechniquesGame Theory and Voting Systems

Cited by 21

Robust preprocessing for health care monitoring framework

Ahmad, N. F., Hoang, D. B., & Phung, M. H. (2009) · 2009 11th International Conference on e-Health Networking, Applications and Services (Healthcom)

Wireless Sensor Networks for Data AnalysisNon-Invasive Vital Sign Monitoring

Cited by 21

Playgrounds and Prejudices: Exploring Biases in Generative AI For Children.

Baines, A., Gruia, L., Collyer-Hoar, G., & Rubegni, E. (2024) · Proceedings of the 23rd Annual ACM Interaction Design and Children Conference

Ethics and Social Impacts of AITechnology's Impact on Media

Cited by 21

Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models

Nezhurina, M., Cipolina-Kun, L., Cherti, M., & Jitsev, J. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 21

An Automated Feedback System Based on Adaptive Testing: Extending the Model

Barker, T. (2010) · International Journal of Emerging Technologies in Learning (iJET)

Intelligent Tutoring Systems and Adaptive LearningEducational Technology and Assessment

Cited by 21

Why is facial expression analysis in the wild challenging?

Gehrig, T., & Ekenel, H. K. (2013) · Proceedings of the 2013 on Emotion recognition in the wild challenge and workshop

Emotion and Mood RecognitionFace recognition and analysis

Cited by 21

Real-Time Railway Hazard Detection Using Distributed Acoustic Sensing and Hybrid Ensemble Learning

Yürekli, Y., Özarpa, C., & Avcı, İ. (2025) · Sensors

Seismology and Earthquake StudiesAdvanced Fiber Optic Sensors

Cited by 21

Continual learning of longitudinal health records

Armstrong, J., & Clifton, D. A. (2022) · 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

Machine Learning in HealthcareDomain Adaptation and Few-Shot Learning

Cited by 21

Simultaneous Segmentation of Fetal Hearts and Lungs for Medical Ultrasound Images via an Efficient Multi-scale Model Integrated With Attention Mechanism

Xi, J., Chen, J., Wang, Z., Ta, D., Lu, B., Deng, X., Li, X., & Huang, Q. (2021) · Ultrasonic Imaging

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 21

Replay-Guided Adversarial Environment Design

Jiang, M., Dennis, M., Parker-Holder, J., Foerster, J., Grefenstette, E., & Rocktäschel, T. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 21

Achieving RBAC on RESTful APIs for Mobile Apps Using FHIR

Rivera Sanchez, Y. K., Demurjian, S. A., & Baihan, M. S. (2017) · 2017 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)

Access Control and TrustElectronic Health Records Systems

Cited by 21

Machine learning systems and intelligent applications

Benton, W. C. (2020) · IEEE Software

Artificial Intelligence ApplicationsSoftware Engineering Techniques and Practices

Cited by 21

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment

Ji, Z., Shaikh, M. A., Moukheiber, D., Srihari, S. N., Peng, Y., & Gao, M. (2021) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 21

Ethical Chatbot Design for Reducing Negative Effects of Biased Data and Unethical Conversations

Bang, J., Kim, S., Nam, J. W., & Yang, D.-G. (2021) · 2021 International Conference on Platform Technology and Service (PlatCon)

Ethics and Social Impacts of AIAI in Service Interactions

Cited by 21

Assessing the net benefit of machine learning models in the presence of resource constraints

Singh, K., Shah, N. H., & Vickers, A. J. (2023) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 21

Congestion control mechanism for ATM networks using neural networks

Tarraf, A. A., Habib, I. W., & Saadawi, T. N. (2002) · Proceedings IEEE International Conference on Communications ICC '95

Network Traffic and Congestion ControlTraffic control and management

Cited by 21

Attribute-Based Encryption and Sticky Policies for Data Access Control in a Smart Home Scenario: A Comparison on Networked Smart Object Middleware

Sicari, S., Rizzardi, A., Dini, G., Perazzo, P., La Manna, M., & Coen-Porisini, A. (2021) · International Journal of Information Security

Cryptography and Data SecurityAccess Control and Trust

Cited by 21

Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU

Shickel, B., Davoudi, A., Ozrazgat-Baslanti, T., Ruppert, M., Bihorac, A., & Rashidi, P. (2021) · Frontiers in Digital Health

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 21

On Linear Identifiability of Learned Representations

Roeder, G., Metz, L., & Kingma, D. P. (2020) · arXiv

Neural Networks and ApplicationsBlind Source Separation Techniques

Cited by 21

Dynamic Time Quantum Priority Based Round Robin for Load Balancing In Cloud Environment

Ghosh, S., & Banerjee, C. (2018) · 2018 Fourth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)

Cloud Computing and Resource ManagementDistributed and Parallel Computing Systems

Cited by 21

Calibrating Large Language Models with Sample Consistency

Lyu, Q., Shridhar, K., Malaviya, C., Zhang, L., Elazar, Y., Tandon, N., Apidianaki, M., Sachan, M., & Callison-Burch, C. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 21

LAB-Bench: Measuring Capabilities of Language Models for Biology Research

Laurent, J. M., Janizek, J. D., Ruzo, M., Hinks, M. M., Hammerling, M. J., Narayanan, S., Ponnapati, M., White, A. D., & Rodriques, S. G. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 21

Examining Ethical Aspects of AI: Addressing Bias and Equity in the Discipline

Shuford, J. (2024) · Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 21

Building, Shifting, & Employing Power: A Taxonomy of Responses From Below to Algorithmic Harm

DeVrio, A., Eslami, M., & Holstein, K. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 21