A Collection of Innovations in Medical AI for patient records in 2024

The field of Artificial Intelligence in healthcare is evolving at an unprecedented pace, driven by rapid advancements in machine learning and the recent breakthroughs in large language models. While these innovations hold immense potential to transform clinical decision making, diagnostics, and patient care, the accelerating speed of AI development has outpaced traditional academic publishing cycles. As a result, many scholarly contributions quickly become outdated, failing to capture the latest state of the art methodologies and their real world implications. This paper advocates for a new category of academic publications an annualized citation framework that prioritizes the most recent AI driven healthcare innovations. By systematically referencing the breakthroughs of the year, such papers would ensure that research remains current, fostering a more adaptive and informed discourse. This approach not only enhances the relevance of AI research in healthcare but also provides a more accurate reflection of the fields ongoing evolution.

@article{zhang2025_2503.05768,
  title={ A Collection of Innovations in Medical AI for patient records in 2024 },
  author={ Yuanyun Zhang and Shi Li },
  journal={arXiv preprint arXiv:2503.05768},
  year={ 2025 }
}