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Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57899, first published .
Medical team discusses data on a monitor, showcasing healthcare technology and innovation.

Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study

Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study

Journals

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  2. Leinert C, Brefka S, Fotteler M, Mueller-Stierlin A, Gebhard F, Rahbari N, Bolenz C, Kestler H, Dallmeier D, Denkinger M, Kocar T. Standard-of-care vs expert-recommended discharge destinations for geriatric surgical inpatients: a prospective observational cohort study. European Geriatric Medicine 2025;17(1):323 View
  3. Rezaeian O, Ghorbanichemazkati E, Bayrak A, Asan O. Clinician perspectives on trust and adoption of AI in breast cancer diagnosis. IISE Transactions on Healthcare Systems Engineering 2026;16(1):32 View
  4. Basile G, Bolcato V, Bambagiotti G, Bianco Prevot L, Tronconi L. When Intuition Meets the Algorithm: Medico-Legal Implications of Artificial Intelligence-Driven Decision-Making in Orthopedics. Bioengineering 2026;13(2):227 View
  5. Borat S, Chowdhury S. Artificial intelligence-driven clinical decision support systems for precision oncology: A comprehensive review. In Silico Research in Biomedicine 2026;2:100265 View
  6. Bose S, Prakash A, Prusty A, Verma R, Padmavathy K, Iragamreddy V. Artificial Intelligence (AI) Supported Decision-Making in Intensive Care Units: Implications for Nursing and Medical Practice. Cureus 2026 View
  7. Veisimankali M, Alimohammadzadeh K, Begloo-Amin G, Bahadori M, Abbaszadeh A. Reimagining nursing practice in the era of AI: a qualitative systematic review and meta-synthesis of nurses’ lived experiences. Journal of Health, Population and Nutrition 2026;45(1) View
  8. Zhang Q, Yan R, Liu X, Li W, Xue X. Performance Comparison Between Domestic and International Large Language Models in Patient Education for Chinese Patients with Lumbar Disc Herniation: A Cross-Sectional Study. DIGITAL HEALTH 2026;12 View
  9. Wang Z, Hu J, Zheng X. Stakeholder Perspectives on AI-Assisted Pain Assessment in Pediatrics: A Qualitative Study of Shared Needs and Divergent Priorities. The Journal of Pain 2026:106415 View