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<p>Artificial intelligence is revolutionizing neurosurgery, with innovative at every stage of practice, right from diagnosis to postoperative care. AI does best in the preoperative stage of planning where medical data depicted by MRI and CT scans are processed through machine learning and deep-learning algorithms that help improve diagnostic accuracy and prognosis. Artificial intelligence helps in intraoperative decision making whereby real-time imaging processed by AI systems significantly enhances the neurosurgeon's ability to effect sharp resections with minimal harm to eloquent areas. Other AI-powered robotic systems, such as the Da Vinci surgical system, further enhance the precision of surgery. In the postoperative period, AI-powered tools monitor patient outcomes for subtle patterns in the data that suggest complications and thus allow early interventions. Full use of AI in neurosurgery may be restricted because of issues related to patient privacy, biased data, and ethical problems. While prospects may yet arise for AI-driven personalized and autonomous surgery, success here is going to require neurosurgeons, AI developers, and ethicists to successfully meet these challenges collaboratively.</p>

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Integrating AI into neurosurgical decisions: a new Frontier in medicine

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月5日

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  • Kashif Munir

摘要

Artificial intelligence is revolutionizing neurosurgery, with innovative at every stage of practice, right from diagnosis to postoperative care. AI does best in the preoperative stage of planning where medical data depicted by MRI and CT scans are processed through machine learning and deep-learning algorithms that help improve diagnostic accuracy and prognosis. Artificial intelligence helps in intraoperative decision making whereby real-time imaging processed by AI systems significantly enhances the neurosurgeon's ability to effect sharp resections with minimal harm to eloquent areas. Other AI-powered robotic systems, such as the Da Vinci surgical system, further enhance the precision of surgery. In the postoperative period, AI-powered tools monitor patient outcomes for subtle patterns in the data that suggest complications and thus allow early interventions. Full use of AI in neurosurgery may be restricted because of issues related to patient privacy, biased data, and ethical problems. While prospects may yet arise for AI-driven personalized and autonomous surgery, success here is going to require neurosurgeons, AI developers, and ethicists to successfully meet these challenges collaboratively.