Digital Transformation of Cancer Care in the Era of Big Data, Artificial Intelligence and Data-Driven Interventions: Navigating the Field

Nikolaos Papachristou*, Grigorios Kotronoulas, Nikolaos Dikaios, Sarah J. Allison, Harietta Eleftherochorinou, Taranpreet Rai, Holger Kunz, Payam Barnaghi, Christine Miaskowski, Panagiotis D. Bamidis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Objectives
To navigate the field of digital cancer care and define and discuss key aspects and applications of big data analytics, artificial intelligence (AI), and data-driven interventions.

Data Sources
Peer-reviewed scientific publications and expert opinion.

Conclusion
The digital transformation of cancer care, enabled by big data analytics, AI, and data-driven interventions, presents a significant opportunity to revolutionize the field. An increased understanding of the lifecycle and ethics of data-driven interventions will enhance development of innovative and applicable products to advance digital cancer care services.

Implications for Nursing Practice
As digital technologies become integrated into cancer care, nurse practitioners and scientists will be required to increase their knowledge and skills to effectively use these tools to the patient's benefit. An enhanced understanding of the core concepts of AI and big data, confident use of digital health platforms, and ability to interpret the outputs of data-driven interventions are key competencies. Nurses in oncology will play a crucial role in patient education around big data and AI, with a focus on addressing any arising questions, concerns, or misconceptions to foster trust in these technologies. Successful integration of data-driven innovations into oncology nursing practice will empower practitioners to deliver more personalized, effective, and evidence-based care.
Original languageEnglish
Article number151433
Number of pages10
JournalSeminars in Oncology Nursing
Volume39
Issue number3
Early online date1 May 2023
DOIs
Publication statusPublished - 1 Jun 2023

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