AIMC Topic: Curriculum

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Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study.

JMIR formative research
BACKGROUND: Clinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for ...

Knowledge and perception of artificial lntelligence education among undergraduate healthcare students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is gaining recognition for its ability to enhance patient outcomes in healthcare. Therefore, integrating AI into the undergraduate curriculum is essential to equip students with foundational knowledge before g...

Medical undergraduate students' awareness and perspectives on artificial intelligence: A developing nation's context.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, yet its integration into medical education remains limited. This study assesses undergraduate healthcare students' knowledge and perceptions of AI, its applications, challenges, and th...

Artificial intelligence and regional anesthesiology education curriculum development: navigating the digital noise.

Regional anesthesia and pain medicine
Artificial intelligence (AI) has demonstrated a disruptive ability to enhance and transform clinical medicine. While the dexterous nature of anesthesiology work offers some protections from AI clinical assimilation, this technology will ultimately im...

Enhancing AI literacy in undergraduate pre-medical education through student associations: an educational intervention.

BMC medical education
BACKGROUND: The integration of artificial intelligence (AI) into healthcare is rapidly advancing, with profound implications for medical practice. However, a gap exists in formal AI education for pre-medical students. This study evaluates the effecti...

Understanding and acceptance of open, laparoscopic, and robotic surgery among nursing students: implications for educational curricula based on a mixed-methods study.

Journal of robotic surgery
This study aimed to assess university nursing students' knowledge and perceptions of open, laparoscopic, and robotic surgery applications. A simultaneous sequential nested quantitative-qualitative hybrid research method design was conducted. The sub-...

Preparing Tomorrow's Physicians: The Case for Machine Learning in Medical Education.

Journal of medical systems
Machine learning should be integrated into medical curricula to prepare physicians-in-training for 21st-century practice conditions. This comment proposes practical implementation strategies that build upon existing educational frameworks by drawing ...

Assessing medical students' readiness for artificial intelligence after pre-clinical training.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is becoming increasingly relevant in healthcare, necessitating healthcare professionals' proficiency in its use. Medical students and practitioners require fundamental understanding and skills development to m...

Learning to care, caring to learn: the evolving nature of medical education.

The New Zealand medical journal
As Otago Medical School marks its 150th anniversary, this paper reflects on what it means to train doctors for both today and the decades ahead. It traces the school's evolution from its nineteenth-century foundations through key innovations in curri...

A Comparative Bicentric Study on Ultrasound Education for Students: App- and AI-Supported Learning Versus Traditional Hands-on Instruction (AI-Teach Study).

Academic radiology
BACKGROUND: The integration of artificial intelligence (AI) into medical education presents significant opportunities for enhancing teaching methods and student learning outcomes. Despite its potential benefits, the implementation of AI in curricula ...