The role of an EIR
Mentor INSTRUCTOR
For attending faculty physicians, DZ-EIR enhances mentorship efficiency with the Agenda-Generator. This tool quickly summarizes check-ins by analyzing thousands of interactions across various dates to identify top wins, challenges, and recommendations—all within 30 seconds. By producing a concise one-sheeter for each mentor, the Agenda Generator ensures that faculty are optimally prepared for meaningful interventions, enabling them to focus on nurturing the next generation of medical professionals.
MENTEE STUDENT
For medical students, DZ-EIR provides the Action-Plan, a crucial tool for managing the rigorous demands of medical training. Within just 10 seconds, the Action Plan helps students structure their tasks—necessary for successful residency placements—by offering research-backed suggestions to enhance productivity and learning outcomes. This immediate support in task management allows students to efficiently plan and adjust their learning strategies, facilitating a more focused and effective educational journey.
Administrator
The Department of Medical Education benefits from the Emotional-Intelligence (EI) Insights view with DZ-EIR. This view dives deep into unstructured data, analyzing historical check-ins across multiple departments to extract and highlight key indicators of emotional intelligence, such as engagement, communication, and mood insights. Additionally, DZ-EIR identifies expression insights across 53 different emotions. This capability allows administrators to focus on developing curricula that foster both academic and emotional growth, without the need to manually sift through vast amounts of data.
Our approach to generative-AI
GENERAL KNOWLEDGE
Our foundational model, powered by OpenAI GPT-4o, sets the baseline for robust and reliable AI interactions within the educational environment. Leveraging the most advanced and extensively researched AI capabilities, this model underpins our platform with safety moderation, general analysis, and extensive information retrieval. It serves as the core engine, ensuring that our AI not only accesses but also interprets vast amounts of information accurately and responsibly.
HUMAN EXPRESSIONS
The expression model, facilitated by HumeAI, measures 53 expressions identified through the subtleties of emotional language and 48 expressions discerned from facial cues, vocal bursts, and speech prosody. By analyzing emotional expressions across text, audio, and video check-ins, our system is able to understand and react to the nuanced emotional landscape of users, fostering a more empathetic mentorship, grounded in the cognitive sciences.
BURNOUT DETECTION
Our specialized burnout detection small-language-model (SLM) is fine-tuned to identify signs of burnout among medical educators and learners. Through reinforcement learning and human feedback (RLHF), this model continually refines its understanding of burnout indicators and solutions, enhancing our platform's ability to support users proactively. This model is integral to our mission of alleviating educational burnout, tailoring interventions that are precise and human-centered.
General Knowledge
OpenAI's advanced AI technology, focusing on aggregating and processing general knowledge to pave the way towards Artificial General Intelligence (AGI)
Human Expressions
HumeAI for precise, scientifically-backed measurements of facial expressions, capturing a spectrum of 53 distinct emotional expressions
Burnout-Detection
Insights into user experience and well-being to develop tool aimed at identifying and addressing burnout, enhancing support for overall societal health.
