Artificial intelligence is making great strides in many sectors of society. In healthcare, medical AI computers are influencing everything from electronic medical records (EMR) use to how hospitals protect themselves from cyberattacks. To support future providers in this digital transformation, schools are increasingly adopting AI for medical education and training.
Transitioning from Traditional Learning to AI Medical Education
Much of traditional training for medical students is memorization-based, sourced from textbooks, lectures, and clinical rotations. This can leave students limited by what they learned at that time and unprepared for the rapidly changing medical landscape, from patient privacy regulations to advancements in robotic surgery.
Medical schools are seeking ways to overcome these limitations. And they’re not just looking for more ways for students to memorize even more information. What if students could perform patient consultations (with real-time feedback!) 24/7? Or have courses tailored to address their specific weaknesses or gaps in their medical knowledge (example: terminology, drug dosages, etc.)
Artificial intelligence, which comprises computer programs and algorithms designed to perform tasks typically performed by people, can perform these and more.
AI used this way is not just for medical students. Medical instructors also benefit from AI in medical education and training, which can aid in everything from lesson planning to assessing students' preparedness for major examinations such as the United States Medical Licensing Examination (USMLE).
AI in Medical Training: Practical Applications
Medical schools and similar facilities build on today’s tech-savvy students, who are already comfortable learning from digital media thanks to computers in schools and smartphone apps. Many applications already used for AI in healthcare, such as generative AI, can be applied to lesson plans and training.
Virtual Patient Visits
Students conduct mock patient visits with AI-generated patients on a medical AI system trained to simulate common symptoms and responses. Instructors then review the transcriptions of the student’s interactions and the diagnosis to determine the student's strengths and areas needing improvement.
Focused Learning
AI can generate draft quizzes and tests for courses, which instructors review for accuracy and comprehension. AI can also grade the materials after students have taken them. Some instructors are using the application to generate new tests tailored to students’ weaknesses, such as medical terminology, and provide support materials.
Surgical Practice
AI is already used in surgery, mainly in the form of surgical robots. To train aspiring surgeons, augmented reality simulations display virtual bodies for practicing procedures. AI is used throughout training, responding to the student’s efforts while collecting data for later review by the student and their instructors.
Benefits of AI in Medical Education and Training
The AI applications described above affect traditional medical education and training in various ways, from facilitating students' access to information to generating new methods for practicing their skills. These provide a variety of benefits:
High-quality Education
Much of medicine is standardized to ensure reliable, measurable outcomes. In medical education, AI reduces subjectivity in grading by instructors, ensuring that each student is assessed using the same metrics. The student can then receive AI-generated, personalized lessons to address any knowledge gaps.
Risk-Free
AI can take the place of patients by drawing on tens of thousands of patient medical records and profiles. Medical students can then practice with these virtual patients, gaining more experience without the costs, risks, and hassles of training with flesh-and-blood patients.
Real-Time Feedback
AI can respond rapidly to medical students’ actions, whether during a lesson or while simulating a virtual patient. The resolution is more likely to remain in the student’s mind, particularly compared with traditional methods, when it is presented hours later during a lecture. Students will then need less training and process more lessons in the same amount of time.
Challenges and Ethical Considerations in AI Medical Education
AI’s capabilities for educating and training medical students are impressive. Those very capabilities also lead to challenges and ethical issues, many of which are unique to the burgeoning technology. Medical schools and training hospitals need to review these issues as part of their due diligence when implementing the technology for students and faculty.
Questionable Information
The AIs may generate incorrect information, ranging from factually false to made-up (the infamous AI “hallucinations”). And many AIs will pass it along very convincingly. Medical students and instructors will need to be diligent in spotting such errors and correcting them. AIs draw on a variety of databases to learn, and erroneous data can rapidly spread to other systems.
No Human Contact
AI for medical training will involve substantial screen time. For example, students could spend hours on medical computers interacting with AI-generated virtual patients. This could reduce the students’ bedside manner and empathy when dealing with real patients, who are far more incoherent.
Learn New Skills
The final challenge schools will face in bringing AI to medical education and training is preparing their instructors. They will need to learn about AI’s capabilities and limitations, such as hallucinations, and how to adapt to current educational methods.
Run AI For Medical Education and Training Worry-Free Thanks to Cybernet
Artificial intelligence offers its strengths across all industries, including healthcare. AI in medical education changes the training of future providers, from virtual foot-steps to real-world procedures like surgery, to personalizing education targeting a student’s strengths and weaknesses.
Contact Cybernet Manufacturing if you are seeking to implement AI in your medical school. Medical computers and tablets, already in use in hospitals, would further enhance medical students' education on how medicine works at their (future) jobs.