Identifiers
Papers
Documents in the 44B Library with Parker Hannifin (United States) on the authorship, newest first.
2026-01-01 · 6 authors here
Harnessing core-accelerated machine learning for enhanced knowledge acquisition in system integration
2025-11-29 · 1 authors here
Privacy-First Data Platform for Financial Services: Integrating Federated Learning, Differential Privacy, and Immutable Audit Trails
2025-11-29 · 1 authors here
Privacy-First Data Platform for Financial Services: Integrating Federated Learning, Differential Privacy, and Immutable Audit Trails
2025-11-28 · 1 authors here
Privacy-First Data Platform for Financial Services: Integrating Federated Learning, Differential Privacy, and Immutable Audit Trails
2025-09-18 · 4 authors here
Structured and Balanced Multicomponent and Multilayer Neural Networks
2025-06-28 · 33 authors here
Patient Perceptions of Artificial Intelligence in Otolaryngology—Head and Neck Surgery: An International Study
2025-05-05 · 2 authors here
Navigating AI Adoption – An “AI Verse” Framework for Enterprises
2025-03-03 · 4 authors here
Advancing laryngology through artificial intelligence: a comprehensive review of implementation frameworks and strategies
2024-09-30 · 1 authors here
Adaptive Neural Feedback Methods for Bias and Weight Adjustment in Feed Forward Layers of LLMs
2024-07-26 · 2 authors here
Fifty years of deceptive marketing research: A systematic review and future research agenda
2024-05-08 · 2 authors here
Applications of ChatGPT in Otolaryngology–Head Neck Surgery: A State of the Art Review
2024-04-26 · 6 authors here
Augmenting Chronic Kidney Disease Diagnosis With Support Vector Machines for Improved Classifier Accuracy
2024-01-17 · 6 authors here
Trust in Machine Learning Driven Clinical Decision Support Tools Among Otolaryngologists
2024-01-01 · 7 authors here
Heart Disease Detection Using Feature Extraction and Artificial Neural Networks: A Sensor-Based Approach
2020-10-06 · 5 authors here
Addressing immediate public coronavirus (COVID-19) concerns through social media: Utilizing Reddit’s AMA as a framework for Public Engagement with Science
Funding
Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.
Who funds this work
Funders named on the papers above. The record holds no recipient field, so this is reached through the documents themselves — and the two columns are two different claims, kept apart.
Under a named grant
funding_awards — the award carries a grant number
Listed as funder
doc_funder_links — named, with no grant number