Introduction: The Unmet Need for Better Data and Less Burden

The digital transformation of healthcare has led to an explosion of electronic health records (EHRs). However, a critical challenge remains: the vast majority of this clinical information is locked away as unstructured "dark data" in free-text notes.

This data is difficult to search, analyse, and leverage for improving clinical decision-making, advancing research, or ensuring continuity of care.

Simultaneously, clinicians are facing an unprecedented administrative burden, spending an enormous amount of time on documentation and coding, which contributes to professional burnout. This reality calls for a paradigm shift — not just to collect data, but to do so more intelligently. This requires a cultural evolution, fostering multi-disciplinary collaboration to bridge the gap between traditional medicine and the new digital tools at our disposal. Artificial Intelligence (AI) is uniquely positioned to address these challenges head-on.

AI's Dual Impact: Structuring Clinical Data and Generating New Medical Insights

AI is emerging as a powerful ally, tackling the data challenge on two major fronts: structuring existing data and using advanced models to generate new insights for both clinicians and patients.