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@ARTICLE{Wichtmann:282951,
      author       = {Wichtmann, Barbara D and Paech, Daniel and Pianykh, Oleg S
                      and Huang, Susie Y and Seltzer, Steven E and Brink, James
                      and Fennessy, Fiona M},
      title        = {{L}eadership in radiology in the era of technological
                      advancements and artificial intelligence.},
      journal      = {European radiology},
      volume       = {36},
      number       = {1},
      issn         = {0938-7994},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DZNE-2025-01412},
      pages        = {548 - 552},
      year         = {2026},
      abstract     = {Radiology has evolved from the pioneering days of X-ray
                      imaging to a field rich in advanced technologies on the cusp
                      of a transformative future driven by artificial intelligence
                      (AI). As imaging workloads grow in volume and complexity,
                      and economic as well as environmental pressures intensify,
                      visionary leadership is needed to navigate the unprecedented
                      challenges and opportunities ahead. Leveraging its strengths
                      in automation, accuracy and objectivity, AI will profoundly
                      impact all aspects of radiology practice-from workflow
                      management, to imaging, diagnostics, reporting and
                      data-driven analytics-freeing radiologists to focus on
                      value-driven tasks that improve patient care. However,
                      successful AI integration requires strong leadership and
                      robust governance structures to oversee algorithm
                      evaluation, deployment, and ongoing maintenance, steering
                      the transition from static to continuous learning systems.
                      The vision of a 'diagnostic cockpit' that integrates
                      multidimensional data for quantitative precision diagnoses
                      depends on visionary leadership that fosters innovation and
                      interdisciplinary collaboration. Through administrative
                      automation, precision medicine, and predictive analytics, AI
                      can enhance operational efficiency, reduce administrative
                      burden, and optimize resource allocation, leading to
                      substantial cost reductions. Leaders need to understand not
                      only the technical aspects but also the complex human,
                      administrative, and organizational challenges of AI's
                      implementation. Establishing sound governance and
                      organizational frameworks will be essential to ensure
                      ethical compliance and appropriate oversight of AI
                      algorithms. As radiology advances toward this AI-driven
                      future, leaders must cultivate an environment where
                      technology enhances rather than replaces human skills,
                      upholding an unwavering commitment to human-centered care.
                      Their vision will define radiology's pioneering role in
                      AI-enabled healthcare transformation. KEY POINTS: Question
                      Artificial intelligence (AI) will transform radiology,
                      improving workflow efficiency, reducing administrative
                      burden, and optimizing resource allocation to meet imaging
                      workloads' increasing complexity and volume. Findings Strong
                      leadership and governance ensure ethical deployment of AI,
                      steering the transition from static to continuous learning
                      systems while fostering interdisciplinary innovation and
                      collaboration. Clinical relevance Visionary leaders must
                      harness AI to enhance, rather than replace, the role of
                      professionals in radiology, advancing human-centered care
                      while pioneering healthcare transformation.},
      subtyp        = {Review Article},
      keywords     = {Artificial Intelligence / Humans / Leadership / Radiology:
                      organization $\&$ administration / Radiology: trends /
                      Artificial Intelligence (Other) / Governance (Other) /
                      Leadership (Other) / Radiology (Other) / Workflow (Other)},
      cin          = {AG Radbruch},
      ddc          = {610},
      cid          = {I:(DE-2719)5000075},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40579558},
      doi          = {10.1007/s00330-025-11745-4},
      url          = {https://pub.dzne.de/record/282951},
}