The rapid development of artificial intelligence has constantly reshaped the field of intelligent healthcare and medicine. As a vital technology, multimodal learning has increasingly garnered interest because of data complementarity, comprehensive information fusion, and great application potential. Currently, numerous researchers are dedicating their attention to this field, conducting extensive studies and constructing abundant intelligent systems. Naturally, an open question arises that has multimodal learning delivered universal intelligence in healthcare? To answer this question, we adopt three unique viewpoints for a holistic analysis. Firstly, we conduct a comprehensive survey of the current progress of medical multimodal learning from the perspectives of datasets, task-oriented methods, and universal foundation models. Based on them, we further discuss the proposed question from five issues to explore the real impacts of advanced techniques in healthcare, from data and technologies to performance and ethics. The answer is that current technologies have NOT achieved universal intelligence and there remains a significant journey to undertake. Finally, in light of the above reviews and discussions, we point out ten potential directions for exploration to promote multimodal fusion technologies in the domain, towards the goal of universal intelligence in healthcare.

中文翻译：

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多模式学习是否为医疗保健行业提供了通用智能？全面调查


人工智能的快速发展不断重塑智能医疗领域。多模态学习作为一项至关重要的技术，由于数据互补性、全面的信息融合和巨大的应用潜力而越来越受到关注。目前，许多研究人员正在将注意力投入到这一领域，进行广泛的研究并构建了丰富的智能系统。自然而然地，一个悬而未决的问题出现了，即多模式学习是否为医疗保健领域提供了通用智能？为了回答这个问题，我们采用三种独特的观点进行整体分析。首先，我们从数据集、面向任务的方法和通用基础模型的角度对医学多模态学习的现状进行了全面综述;基于它们，我们进一步讨论了五个问题中提出的问题，以探讨先进技术在医疗保健中的真正影响，从数据和技术到绩效和道德。答案是，当前的技术尚未实现通用智能，还有一段重要的旅程要进行。最后，结合上述回顾和讨论，我们指出了推动该领域多模态融合技术的十个潜在探索方向，以实现医疗保健普遍智能的目标。