ReviewFrontiers in medicine2025
From "teaching by word and deed" to "intelligent mentorship": ethical reconsiderations of AI-enabled medical education - lessons from China.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Cognitive reshaping and resurgence of humanness: restructuring the medical education continuum in the era of generative AI.Frontiers in medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI), as a major driving force of the Fourth Industrial Revolution, is profoundly reshaping the landscape of medical education. Driven by the extensive use of intelligent algorithms, big data analysis, and virtual simulation, a new "fourth-generation medical education" is taking shape, emphasizing health orientation, interdisciplinary integration, and intelligent empowerment. The application of AI in medical education significantly enhances instructional efficiency and personalization, advancing reforms in lesson planning, curriculum design, and virtual clinical simulation. However, an inherent tension exists between the humanistic nature of medical education and the mechanical logic of AI: its integration into teaching may cause alienation in teacher-student relationships, weakening of medical humanism, and ethical dilemmas such as algorithmic bias and privacy infringement. Taking China's medical education practices as an example, this paper systematically examines the ethical challenges of AI-enabled medical education and proposes a three-dimensional ethical reconstruction framework: (1) reshaping teacher-student relationships to preserve the balance between teaching and learning; (2) reinforcing medical humanism to safeguard the compassionate essence of education; and (3) improving ethical governance through coordinated efforts among government, society, hospitals, and universities. The sustainable development of AI-empowered medical education lies in upholding the moral essence of "humanity within intelligence," preserving the warmth of "teaching by word and deed" while integrating technological rationality with humanistic care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.