Artificial intelligence (AI) for science (AI4S) technology, the AI technology for scientific research, has shown tremendous potential and influence in the field of healthcare, redefining the research paradigm of medical science under the guidance of computational medicine. We reviewed the main technological trends of AI4S in reshaping healthcare paradigm: knowledge-driven AI, leveraging extensive literature mining and data integration, emerges an important tool for understanding disease mechanisms and facilitating novel drug development; data-driven AI, delving into clinical and human-related omics data, unveils individual variances and disease mechanisms, and further establishes patient-centric digital twins to guide drug development and personalized medicine. Meanwhile, based on authentic patient digital twin models, adaptable strategies are employed to further propel the development of "e-drugs" that mimic the authentic mechanisms. These digital twins of drugs are evaluated for drug efficacy and safety through large-scale cloud-based virtual clinical trials, and followed by rationally designed real-world clinical trials, thus notably reducing drug development costs and enhancing success rates. Despite encountering challenges such as data scale, quality control, model interpretability, the transition from science insights to engineering solutions, and regulatory hurdles, we anticipate the integration of AI4S technology to revolutionize drug development and clinical practices. This transformation brings revolutionary changes to the medical field, offering novel opportunities and challenges for the development of medical science, and more importantly, providing necessary but personalized healthcare solutions for humankind.
The innovative behavior of clinical nurses is of great significance for the professional development of nurses and the improvement of nursing service quality. This research topic has received continuous attention from domestic and foreign scholars. There is still significant room for improvement in the level of innovative behavior among clinical nurses in China. Constructing effective interventions to enhance innovative behavior among clinical nurses in China is an urgent requirement to promote the development of nursing informatization and nursing quality. This article reviews the intervention forms, theoretical support, effectiveness, and limitations of innovative behaviors among clinical nurses both domestically and internationally. It proposes prospects for future intervention plans, aiming to provide ideas and references for nursing managers to develop tailored, scientific, and effective intervention strategies.