Advances in nano research

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Integrating Nano-AI predictive models for postoperative risk assessment in spinal fusion

  • Li Chunhui (Department of Neurosurgery, The First Hospital of Hunan University of Chinese Medicine) ;
  • Zhang Wenjia (Department of Neurosurgery, The First Hospital of Hunan University of Chinese Medicine) ;
  • Wu Yue (Beijing Chaoyang Hospital, Capital Medical University)
  • Received : 2025.02.05
  • Accepted : 2025.09.01
  • Published : 2025.09.25
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Abstract

Nanotechnology has created new opportunities in precision medicine, providing a chance to monitor the biological signals, molecular markers, and micro-environmental changes at the ultrasensitive level, which occurs before complications. The issue of postoperative complications that arise after performing spinal fusion surgeries is a burning clinical issue, and most of the time, it brings about long-term recovery, increased healthcare expenses, and deteriorated patient outcomes. We suggest the incorporation of nano-enabled AI prediction models in this work that utilizes data collected by nano-sensors, nanomaterials-based diagnostics, and traditional clinical data to improve risk stratification in spinal fusion. Working on a nanoscale, these systems bead on minor physiological changes, including inflammatory biomarkers, metabolic changes, and tissue healing, obscured by conventional techniques. Combined with artificial intelligence, nano-derived datasets offer unmatched granularity, increasing the forecasting performance and allowing timely detection of patients who are at a significant risk of unfavorable events. This model of Nano-AI fills the gap between nano-medicine and computational modeling to provide an innovative solution to customized care postoperative. Finally, the nano-integrated predictive analytics can transform the paradigm of surgical risk assessment, which will inform proactive solutions and support patient safety in sophisticated spinal surgeries.

Keywords

Acknowledgement

Natural Science Founndationn of Hunan Province (2025JJ80923), Hunan Provincial Health Commission 2023 Health Appropriate Technology Promotion Project (202319019034).

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