Overcoming Knowledge Gaps with AI: A Solution for Medical Students

Medical school is a laborious journey, with seemingly endless amounts of information to master. The sheer quantity of knowledge can be overwhelming, and making appropriate treatment and diagnosis decisions can be difficult. Historically, medical students have used books, lectures, flashcards, and collaboration with professors and peers to fill their knowledge gaps. While this is still essential to the learning process, knowledge gaps can also be addressed with improved natural language processing algorithms. Artificial intelligence (AI) is revolutionizing how medical students (and the world) learn and retain information, and can be an essential tool to efficient and effective knowledge acquisition. In this blog, we’ll explore how medical students can incorporate AI-powered study tools to enhance their learning and improve knowledge retention.

Medical School Challenges and AI Study Tools – Opportunities for Efficiency

At each stage of medical education, there is a persistent feeling of learning and forgetting information. Whether it be the Krebs cycle (for the 10th time) or the appropriate STEMI treatment, remembering the intricacies of every pathway is nearly impossible. Medical education requires significant amounts of memorization as well as a level of understanding required to apply this “memorized” knowledge. Traditional studying methods are incredibly valuable, and serve as the foundation for how we learn today. However, these methods take significant amounts of time, which is often lacking in the busy schedule of medical students. This leaves students searching for more efficient methods of studying and understanding that are difficult to address in the limited time available.

How AI is Transforming Medical Education

The ever-increasing amounts of information, coupled with pressure to perform in the clinical and testing environment can create significant stress, burnout, and underperformance. With this increasing pressure, there also seems to be an increasing amount of resources available. While study adjuncts can be helpful, there is an overwhelming amount of information thrown at medical students daily. Sifting through this information takes significant time and resources, which most students cannot afford in their busy schedules. The advent of natural language processing (NLP) algorithms such as ChatGPT, Claude, and OpenEvidence have revolutionized how humans interact with the swaths of internet information. Instead of google searches with 10,000 results, these NLP models can provide targeted answers to the most specific questions. ChatGPT has even shown success in passing medical board exams, a feat that requires significant time, stress, and resources for the average medical student. 

While these NLP algorithms are far from perfect, they hold promise in maximizing efficiency and filling knowledge gaps better than most professors, google searches, or peers. Effectively leveraging these models can help maximize learning in an efficient manner, allowing medical students to focus on their clinical goals and information retention rather than information finding. Below, we discuss multiple methods by which artificial intelligence can be used to fill knowledge gaps for medical students. 

Interactive Case Studies

Generative AI can provide realistic patient scenarios, which can augment critical thinking and decision making in realistic patient scenarios. A commonly tested case is that of acute coronary syndrome, and many medical students are expected to know ACLS algorithms inside and out. Instead of memorizing an algorithm and hoping this translates to the clinical environment, ChatGPT has shown accuracy in simulating ACLS scenarios to better bridge preclinical and clinical training. This integrated approach provides integrated practice that improves both knowledge and its implementation in the clinical environment. Another useful method of case study utilization for learning is that of identifying knowledge gaps. While simulating a case study, these generative AI models can identify treatment errors and provide supportive reasoning. Thus, it not only walks a student through a case, but provides free and real-time feedback for improvement of medical knowledge and clinical performance. 

Synthesizing medical literature

There are often times practice standards are tested (vaccine administration, hyperlipidemia management, etc). A known problem with many NLP tools is that of hallucinations, where the model produces its own fabricated sources. A key tool that can help summarize medical literature accurately is OpenEvidence, which is specifically engineered to provide accurate citations while summarizing key findings. This can not only help with studying for exams, but can also assist in the diagnosis and treatment of many conditions encountered on the wards each day. This not only improves patient care and time to effective treatment, but also makes the medical student look engaged, knowledgeable, and invested in each pathology. 

Question production and augmentation

Medical students are often concerned about using up gold-standard resources before they are prepared to enter dedicated study. In addition, some students wish they had more questions on a specific topic to master a certain concept or pathway. Much of the time, available qbanks do not have simple ways to search for specific topics. In addition, there are finite amounts of questions to answer. NLP models, on the other hand, can be leveraged to produce high quality practice questions for almost any medical concept. With appropriate prompting, ChatGPT can provide USMLE style questions with thorough answer explanations on specific topics. This can augment the use of those precious resources, while also enhancing student understanding of specific topics that require more study. 

AI Productivity study tools and time management

Aside from directly producing study materials and information, these AI models can also help with study schedules and time management. Studying for a shelf or board exam can be overwhelming, and many students often struggle with how to start. NLP models can assist with personalized study plans to fit a range of times and schedules. In addition, they can suggest study structure and strategies, and even incorporate time for exercise, meal preparation, and more. Optimizing time management can increase the amount of studying and preparation that can be accomplished within a given time. Thus, even if books and peer/professor discussions are preferred, AI can still augment the learning and knowledge acquisition of the busy medical student. 

Best Practices for Using AI Study Tools

The world of AI can seem overwhelming. A great place to start includes these best practices, which include optimal methods for the integration of AI into the busy medical school student life:

1. Integration with Traditional Methods: Combine AI tools with conventional study methods like textbooks, tutoring and group discussions. AI should complement, not replace, proven learning techniques. In addition, the source of information (trusted publications versus AI-generated) should be a strong consideration when studying for key exams.
2. Regular Progress Monitoring: Take advantage of AI analytics to track your progress and identify trending areas of difficulty. This data can help you adjust your study strategy effectively.
3. Active Engagement: Don’t passively consume AI-generated content. Engage with interactive features and challenge yourself to explain concepts in your own words. Use the AI as a tool to test yourself, have the AI provide feedback on explanations you provide on challanging topics. AI can help you hone your skills, which will ultimately make you a better clinician!
4. Feedback Utilization: Pay attention to AI-generated feedback and explanations. Use this information to deepen your understanding and correct misconceptions. 
5. Don’t be afraid to try multiple methods: Each student is different, and learns in different ways. AI is a dynamic tool that can fit into the study schedule of each student. If a certain method isn’t working, try something else!

Limitations and Considerations

While AI tools offer numerous benefits, it’s important to acknowledge their limitations:

• AI cannot replace human mentorship and clinical experience. These relationships are essential for a full medical school experience, and to get the most out of your rotations.
• Some tools may have gaps in their knowledge bases. If something seems wrong, don’t be afraid to question it. AI should be used as a tool rather than an all-knowing entity.
• Tools are constantly changing, and models are continuously evolving. Inconsistencies may result with this ever-changing environment, but this is not a reason to stop using these AI study tools!
• Clinical expertise reigns. Despite the vast knowledge available on the internet, your attendings and residents have invaluable lived experiences. Their wisdom is essential to becoming a knowledgeable and well-rounded clinician. AI-generated information should serve as a conversation starter to learn more about how the information fits into your specific practice. 

Conclusion

AI study tools represent a powerful solution for medical students looking to overcome knowledge gaps and enhance their learning efficiency. By combining artificial intelligence with traditional study methods, students can create a more effective and personalized learning experience at all stages of their medical education.

The key to success lies in using these tools strategically while maintaining a balance with conventional medical education approaches. As AI technology continues to evolve, medical students who embrace these innovations while remaining grounded in fundamental medical principles will be best positioned for success in their medical careers.

For medical students feeling overwhelmed by the vast amount of knowledge required, AI tools offer hope and practical solutions. By leveraging these technologies effectively, students can identify and address their knowledge gaps more efficiently, ultimately becoming more competent and confident medical professionals.

Remember, the goal isn’t just to memorize information but to develop a deep understanding that will translate into better patient care. AI study tools are becoming an increasingly valuable asset in achieving this important objective.