M3H: Multimodal Multitask Machine Learning for Healthcare

arXiv:2404.18975v1 Announce Type: new
Abstract: Recent breakthroughs in AI are poised to fundamentally enhance our study and understanding of healthcare. The development of an integrated many-to-many framework that leverages multiple data modality inputs for the analytical modeling of multiple medical tasks, is critical for a unified understanding of modern medicine. In this work, we introduce M3H, an explainable Multimodal Multitask Machine Learning for Healthcare framework that consolidates learning from diverse multimodal inputs across a broad spectrum of medical task categories …

abstract arxiv cs.ai cs.lg data development framework healthcare inputs machine machine learning medical medicine modeling modern multimodal multiple study tasks type understanding work