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Advancing breast cancer clinical management through technological innovation: the potential role of artificial
A Toss1, L Bellardita2, A Botticelli3
1Department of Oncology and Hematology, Azienda Ospedaliero-Universitaria di Modena, Modena, Italy; Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Abstract:
In health care, artificial intelligence (AI) is emerging as a powerful tool to improve the quality of care, support health care professionals, and build a more streamlined and efficient health care system while also enhancing the patient experience. In particular, integrating AI into clinical practice through an innovative management approach like lean and change management could optimize diagnostic and therapeutic pathways, increase operational efficiency within hospitals, and promote more personalized, patient-centered care. At the same time, uncertainty remains about how these new technologies should be implemented in order to become broadly accessible in clinical practice. This expert opinion explores the potential role of AI in breast cancer patients' care from the perspective of a team of Italian opinion leaders. The manuscript identifies two main areas of application: (i) AI solutions designed for direct patient interaction (i.e. conversational agents interacting with patients, providing informational and organizational support during the care journey and contributing to personalized care and improved patient quality of life) and (ii) AI solutions for clinical support to health care providers (i.e. tools or algorithms aimed at supporting physicians, reducing workload, and optimizing operational flows). When implemented alongside lean and change management strategies, these solutions have the potential to streamline care pathways and improve the satisfaction and interaction of patients and health care professionals, ultimately benefiting all stakeholders. The document also addresses the ethical, regulatory, methodological, and educational challenges associated with the implementation of AI solutions in clinical practice.
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