Abdulhadi Shoufan
Health Informatics · 2019–2023
A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Health Informatics — 5 citations into it; #79 of 240 by trust here, #229 by citations
Whom Abdulhadi Shoufan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Fred D. Davis
- V. Venkatesh
- Teo Sušnjak
- Michael G. Morris
- Cemal Aker
- Gordon B. Davis
- José Quiroga Pérez
- Mohammad Amin Kuhail
- Pengfei Liu
- Sinan Kalkan
Who trusts Abdulhadi Shoufan overall
Papers from Abdulhadi Shoufan's perspective
Ordered by how strongly the researchers Abdulhadi Shoufan trusts endorse each paper. Same corpus, a different order for every researcher.
- Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
- User Acceptance of Information Technology: Toward a Unified View (MIS Q.)
- Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
- Chatbots applications in education: A systematic review (Computers and Education: Artificial Intelligence)
- Rediscovering the use of chatbots in education: A systematic literature review (Computer Applications in Engineering Education)
- Chatbots for learning: A review of educational chatbots for the Facebook Messenger (Comput. Educ.)
- Do we need hundreds of classifiers to solve real world classification problems?
- A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT (Proceedings of the 30th Conference on Pattern Languages of Programs)
- Variability in Large Language Models’ Responses to Medical Licensing and Certification Examinations. Comment on “How Does ChatGPT Perform on the United States Medical Licensing Examination? The… (JMIR Medical Education)
- Using deep networks for drone detection
Their papers
- Exploring Students’ Perceptions of ChatGPT: Thematic Analysis and Follow-Up Survey (2023) — 336 citations
- Machine Learning-Based Drone Detection and Classification: State-of-the-Art in Research (2019) — 308 citations