Hongnan Ye
Biographic Data
| ID | 8990578 |
|---|---|
| NAME | Hongnan Ye |
| GIVEN NAMES | Hongnan |
| FAMILY NAME | Ye |
| SIGNATURE | YE H |
| AFFILIATIONS | Beijing Alumni Association of China Medical University |
| ORCID | 0009-0004-9013-2919 |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 9 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Achieving sustainable development goals for health workforce
Dear EditorCampbell et al. (2025) (1) present a timely critique of the misalignment between health workforce education, labor markets, and population health needs. Their call for integrated strateg
From Conscientious Objection to Value‐Neutral Ethical Frameworks and Preventive Medical Education Pathways
Data sharing not applicable as no datasets generated and/or analysed for this study
Other possible perspectives for solving the negative outcome penalty paradox in the application of artificial intelligence in clinical diagnostics
Artificial intelligence (AI), represented by machine learning, artificial neural networks and deep learning, is impacting all areas of medicine, including translational research (from bench to bedside to health policy), clinical medicine (including diagnosis, treatment, prognosis and healthcare resource allocation) and public health. At a time when almost everyone is focused on how to better realise the promise of AI to transform the entire healt…
Suggestions for the use of the ‘yarigai’ story in fostering medical professionalism among medical students
Dear EditorI read the paper by Nishigori et al. [1] with interest. The study provides a new and important tool for identifying the individual doctor’s ‘yarigai’ story in his or her experience of me
Dealing with ethical issues in genomic medicine requires achieving a higher level of consensus and ethical preparedness is not easy to achieve
Address health inequities among human beings is an ethical matter of urgency, whether or not to develop more powerful AI
Three Suggestions for Better Integrating Artificial Intelligence into Nursing Education
Potential challenges to using competency frameworks as a tool for a variety of important decisions related to medical faculty members
Dear EditorIn the paper by Foroughi et al. (2024), the authors insightfully proposed a competency framework with four themes: (1) essential personal competencies, (2) technical/functional competenc
Some suggestions for 'A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (Aitel) research in medical education’
Dear EditorResearchers from various countries have utilized both existing and newly developed AI systems to evaluate their effectiveness in medical education. The results have been consistently pos
No prominent works on this page.
Dealing with ethical issues in genomic medicine requires achieving a higher level of consensus and ethical preparedness is not easy to achieve
Address health inequities among human beings is an ethical matter of urgency, whether or not to develop more powerful AI
Three Suggestions for Better Integrating Artificial Intelligence into Nursing Education
Potential challenges to using competency frameworks as a tool for a variety of important decisions related to medical faculty members
Dear EditorIn the paper by Foroughi et al. (2024), the authors insightfully proposed a competency framework with four themes: (1) essential personal competencies, (2) technical/functional competenc
Some suggestions for 'A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (Aitel) research in medical education’
Dear EditorResearchers from various countries have utilized both existing and newly developed AI systems to evaluate their effectiveness in medical education. The results have been consistently pos
Other possible perspectives for solving the negative outcome penalty paradox in the application of artificial intelligence in clinical diagnostics
Artificial intelligence (AI), represented by machine learning, artificial neural networks and deep learning, is impacting all areas of medicine, including translational research (from bench to bedside to health policy), clinical medicine (including diagnosis, treatment, prognosis and healthcare resource allocation) and public health. At a time when almost everyone is focused on how to better realise the promise of AI to transform the entire healt…
Suggestions for the use of the ‘yarigai’ story in fostering medical professionalism among medical students
Dear EditorI read the paper by Nishigori et al. [1] with interest. The study provides a new and important tool for identifying the individual doctor’s ‘yarigai’ story in his or her experience of me
Achieving sustainable development goals for health workforce
Dear EditorCampbell et al. (2025) (1) present a timely critique of the misalignment between health workforce education, labor markets, and population health needs. Their call for integrated strateg
From Conscientious Objection to Value‐Neutral Ethical Frameworks and Preventive Medical Education Pathways
Data sharing not applicable as no datasets generated and/or analysed for this study
Computer Science (7 works) · Medicine (7 works) · Psychology (6 works) · Engineering (4 works) · Engineering ethics (4 works) · Medical education (4 works) · Political science (4 works) · Artificial Intelligence in Healthcare and Education (3 works) · Healthcare cost, quality, practices (3 works) · Artificial Intelligence (2 works)