2025
AI Reshapes Healthcare
Global event
Artificial Intelligence is reshaping the healthcare sector worldwide. It is revolutionising diagnostics, optimising clinical workflows, and has the potential to develop the future of personalised medicine. AI-driven tools are important in predictive care, where they can assist in early disease detection, treatment optimisation, and patient monitoring. This technological leap is transforming healthcare systems into more efficient, intelligent, and adaptive environments that can better respond to global health challenges.
Societal, political, and scientific relevance
AI tools in healthcare can offer an opportunity to reduce disparities in care, improve access to medical expertise, and optimise resource use. It can also play a key role in creating more sustainable healthcare by enabling data-driven decisions and minimising waste. These benefits are accompanied by urgent ethical questions regarding patient data and accountability, but also about the risks of automated care becoming more widespread.
In this podcast, Niklas Lidströmer introduces his research and the inspiration behind his co-edited title Artificial Intelligence in Medicine, one of the first reference works available on Artificial Intelligence in Medicine. In addition, he provides an overview on how artificial intelligence is currently being used in medicine, and how AI can impact librarianship, such as in administrative support and citation use.
Impact on research and education
As AI becomes more integrated into healthcare, researchers are focused on making it accurate, ethical, and sustainable. Moreover, diverse, high-quality, and securely shared data is needed to train reliable models. Privacy-preserving technologies like federated learning and blockchain are now essential to protect patient information.
Researchers are also working to reduce the environmental impact of digital healthcare by improving energy efficiency. This work requires deeper collaboration across fields, combining medicine, computer science, ethics, and environmental science to ensure AI supports smarter, fairer, and more responsible healthcare for the future.
Role of Springer Nature books
Springer Nature eBooks help researchers keep pace with the rapid evolution of AI in healthcare, offering timely, reliable content that reflects the latest innovations, challenges, and opportunities in the future of AI and medicine. From foundational theories to emerging technologies, like federated learning and ethical AI, these eBook collections always evolve alongside science.
Sustainable Development Goals
This topic aligns with the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 3: Good Health and Well-Being. Organisations interested in supporting these goals can learn more through the SDG 3 book series.
Book highlights
This book explains
how technological innovations are transforming healthcare within the framework of Society 5.0 and next-generation medicine. It explores five key trends—hybrid care models, digitization, AI adoption, cloud-based health systems, and precision medicine—while examining technologies like digital twins, IoT, big data, and blockchain. The authors address legal, ethical, and sustainability challenges, offering guidance for researchers, clinicians, and policymakers on integrating digital solutions responsibly.
This book explains
Artificial Intelligence is driving the evolution from personalized medicine to personalized digital medicine. It begins by exploring AI’s role in biomedical research and patient care, then presents real-world applications such as digital therapeutics, in silico trials, and network pharmacology. Finally, it looks ahead to emerging technologies like blockchain, quantum computing, and the metaverse, while addressing ethical, regulatory, and social implications for personalized healthcare.
This book explains
how modern data science and big data analytics are transforming healthcare by uncovering clinical insights that traditional methods might miss. It emphasizes the role of artificial intelligence in applications ranging from diagnosis to treatment, making it an essential resource for researchers and clinicians seeking to understand and apply AI-driven techniques in real-world medical practice.
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