Phenikaa University

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study

Bach Xuan Tran, Giang Thu Vu, Giang Hai Ha et al.

2019 · 441 Zit.

The limitations of retraction notices and the heroic acts of authors who correct the scholarly record: An analysis of retractions of papers published from 1975 to 2019

Quan‐Hoang Vuong

2019 · 124 Zit.

Artificial Intelligence vs. Natural Stupidity: Evaluating AI Readiness for the Vietnamese Medical Information System

Quan‐Hoang Vuong, Tung Manh Ho, Thu‐Trang Vuong et al.

2019 · 89 Zit.

Understanding the acceptance of emotional artificial intelligence in Japanese healthcare system: A cross-sectional survey of clinic visitors’ attitude

Tung Manh Ho, Ngoc-Thang B. Le, Peter Mantello et al.

2022 · 74 Zit.

Characteristics of retracted articles based on retraction data from online sources through February 2019

Quan‐Hoang Vuong, Viet‐Phuong La, Tung Manh Ho et al.

2020 · 50 Zit.

Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study

Huy Cong Nguyen, Đang Hai, Thuy Linh Nguyen et al.

2025 · 19 Zit.

Three tragedies that shape human life in age of AI and their antidotes

Tung Manh Ho, Manh‐Toan Ho

2025 · 14 Zit.

A preliminary example of utilizing AI text generation to support academic writing “Humans befriending their creations some notes on the human-AI relationship”

Tam-Tri Le

2023 · 14 Zit.

Characteristics of retracted articles based on retraction data from online sources through February 2019

Quan‐Hoang Vuong, Viet‐Phuong La, Tung Manh Ho et al.

2020 · 13 Zit.

Gauging public opinion of AI and emotionalized AI in healthcare: findings from a nationwide survey in Japan

Peter Mantello, Nader Ghotbi, Tung Manh Ho et al.

2024 · 7 Zit.

Artificial intelligence and retracted science

Minh‐Hoang Nguyen, Quan‐Hoang Vuong

2024 · 6 Zit.

Are we at the start of the artificial intelligence era in academic publishing?

Quan‐Hoang Vuong, Viet‐Phuong La, Minh‐Hoang Nguyen et al.

2023 · 4 Zit.

Retraction Data Can Bring More Insights and Implications for Not Just Authors and Their Institutions, but Funders, Policy-Makers, and Editors

Quan‐Hoang Vuong

2019 · 2 Zit.

Benchmarking large-language-model vision capabilities in oral and maxillofacial anatomy: A cross-sectional study

Nguyễn Việt Anh, Thi Quynh Trang Vuong, Nguyễn Văn Hùng

2025 · 2 Zit.

Assessment of the Large Language Models in Creating Dental Board‐Style Questions: A Prospective Cross‐Sectional Study

Nguyễn Việt Anh, Nguyen Thi Trang

2025 · 2 Zit.