EDITORIAL
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January - March 2026
J Gandhara Med Dent Sci
How to cite this editorial
Shehzad S. The Time is Now: Rethinking Medical Education and Health
Research with Articial Intelligence. J Gandhara Med Dent
Sci.2026;13(1):1-2.https://doi.org/10.37762/jgmds.13-1.
THE TIME IS NOW: RETHINKING MEDICAL EDUCATION AND HEALTH RESEARCH WITH
ARTIFICIAL INTELLIGENCE
:
Soa Shehzad
PhD Scholar, Community Dentistry
Sardar Begum Dental College, Peshawar
+92-345-9222232
soashehzad74@gmail.com
Health research and medical education have historically developed along distinct yet interrelated trajectories. While
each eld has its own focus and methodologies, their connection is crucial for advancing me dical knowledge and
improving patient care. Understanding the interplay between research and education is essential for fostering
innovation in healthcare practices. Research oers evidence to inform clinical practice, while medical education
focuses on transmitting established knowledge and skills to future healthcare providers. This linear approach, with
research coming before education, is increasingly misaligned with the realities of modern healthcare. Today’s
clinicians must operate within rapidly evolving systems that demand not only evidence-based practice but also
continuous inquiry, adaptation, and improvement.
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Therefore, integrating health research into medical education is
no longer just an aspiration; it is a necessity. Medical education is a powerful yet often overlooked setting for
health research. Learning environments shape clinical reasoning, professional identity, ethical practice, and
responsiveness to community health needs. When research is integrated into curricula, students move beyond
memorization to inquiry-based thinking, learning to ask questions, analyze data, and evaluate interventions in real-
world situations.
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In this way, education itself functions as a form of health intervention, inuencing quality of care
and system eciency long before graduates practice independently.
The rise of articial intelligence (AI) has accelerated and changed this integration. AI does not replace the
intellectual or ethical foundations of research and education; instead, it improves their interaction. In health
research, AI supports large-scale data analysis, pattern recognition, and rapid evidence synthesis.
3,4,5
In medical
education, it supports learning analytics, personalized feedback, and ongoing curriculum evaluation. When used
intentionally, these functions allow research insights to directly shape educational design, while educational data
raises new research questions about learning, competence, and clinical performance. Signicantly, AI facilitates a
shift from xed curricula to adaptive learning systems that are constantly updated with evidence.
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Educational
interventions, whether simulation, assessment strategies, or hybrid learning models, can now be examined, rened,
and adjusted almost in real time. This transforms medical education into a dynamic laboratory where health
research and teaching continually inform each other through cycles of inquiry and improvement. For learners, this
integration enhances research literacy and critical thinking about evidence. For educators, it promotes scholarly
teaching grounded in data rather than tradition. However, integrating AI without proper governance risks
superficial adoption. Rigorous methods, ethical oversight, and contextual awareness must guide AI-enabled
research and education. Issues such as data privacy, algorithmic bias, and equity are signicant in low - and middle-
income settings, where resources vary and adapting to local contexts is essential.
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Therefore, incorporating AI into
research and education eorts requires faculty development, interdisciplinary collaboration, and institutional
commitment to educational scholarship. The future of medical education does not depend on choosing between
teaching, research, or technology, but on understanding how they depend on one another. Integrating health
research into medical education, with thoughtful support from AI, transforms learners into contributors to
knowledge, educators into scholarly investigators, and institutions into catalysts for health system learning.
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The
collaboration between human creativity and AI signicantly enhances health research. By maintaining a strong
commitment to ethical practices and transparent communication, we are embarking on a journey that brings
together technology and academia, paving the way for a new era of scholarly excellence.
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The real challenge is not
whether this integration should happen but how carefully it is designed, governed, and maintained. In an era of
complexity and uncertainty, teaching solely based on evidence is not enough. Medical education must incorporate
evidence-based methods that blend research and AI to help health professionals learn, adapt, and lead throughout
their careers.
REFERENCES
1. Cullen L, Hanrahan K, Farrington M, Tucker S, Edmonds S. Evidence-based practice in action: Comprehensive strategies, tools, and
tips from University of Iowa Hospitals & Clinics. Sigma Theta Tau International; 2022. ISBN: 9781646480480.
:
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2. Kotsis KT. Integrating inquiry-based learning in the new Greek primary science curriculum. Eur J Educ Pedagogy. 2024;5(6):63–71.
https://doi:10.24018/ejedu.2024.5.6.774.
3. Coiera E, Liu S. Evidence synthesis, digital scribes, and translational challenges for articial intelligence in healthcare. Cell Rep Med.
2022;3(12):100863. https://doi:10.1016/j.xcrm.2022.100863. PMID: 36468749.
4. Mishra S, Takke A, Auti S, Suryavanshi S, Oza M. Role of articial intelligence in health care. BioChemistry: An Indian Journal.
2017;11(5):1–14.
5. Mohanasundari S. Role of articial intelligence in health care and research. Asian J Nurs Educ Res. 2025;15(2):111 –8.
https://doi:10.52711/2349-2996.2025.00025.
6. Strielkowski W, Grebennikova V, Lisovskiy A, Rakhimova G, Vasileva T. AI‐driven adaptive learning for sustainable educational
transformation. Sustain Dev. 2025;33(2):1921–47. doi:10.1002/sd.2810.
7. Joseph J. Algorithmic bias in public health AI: a silent threat to equity in low-resource settings. Front Public Health.
2025;13:1643180.https://doi:10.3389/fpubh.2025.1643180.
8. Ijaz F. Integration of articial intelligence technology in medical education. MedERA J CMH LMC IOD. 2023;5(2):34–8.
9. Shehzad S. Proliferation of Chat GPT into Health Research. J Gandhara Med Dent Sci. 2023 Dec. 31;11(1):1-2.
https://doi.org/10.37762/jgmds.11-1.574
The Time is Now: Rethinking Medical Education
January - March 2026
