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Published on: April 11, 2016
Precision Medicine and Artificial Intelligence in Next-Generation Cancer Surgery: A Comprehensive Analysis of
Alireza Negahi1, Mehdi Khosravi-Mashizi1,2, Hossein Najdsepas1
1Breast Health & Cancer Research Center, Iran University of Medical Sciences, Tehran, Iran.
Background:
Cancer surgery is undergoing transformative integration of precision medicine, artificial intelligence (AI), robotics, advanced imaging, and molecular technologies. These innovations promise enhanced surgical precision, improved patient outcomes, and personalized treatment approaches through data-driven decision-making.
Methods:
A comprehensive systematic literature review was conducted across PubMed, Embase, Cochrane Library, and Web of Science databases from January 2020 to November 2025. Studies were analyzed for clinical applications, therapeutic outcomes, cost-effectiveness, and implementation challenges. Primary endpoints included surgical accuracy, margin status, survival outcomes, complication rates, and technology adoption metrics.
Results:
Precision medicine utilizing genomic profiling and circulating tumor DNA demonstrated 94.9% sensitivity and 88.8% specificity in multi-cancer detection. The CIRCULATE-Japan GALAXY study showed ctDNA positivity during the molecular residual disease window predicted significantly inferior disease-free survival (HR 11.99; P < 0.0001) and overall survival (HR 9.68; P < 0.0001). AI-assisted surgical systems achieved area under the curve values of 0.76-0.85 in outcome prediction and reduced surgical complications by 25-30%. The da Vinci 5 robotic system demonstrated 43% reduction in tissue damage through force feedback technology. Meta-analysis of 15,137 patients showed robotic pancreatoduodenectomy reduced hospital stays and conversion rates compared to laparoscopy. Fluorescence-guided surgery achieved improved 5-year overall survival (80.6% vs. 66.7%, P = 0.018) in gastric cancer. Mass spectrometry techniques achieved 93.4-97.1% diagnostic accuracy. Perioperative immunotherapy in non-small cell lung cancer reduced recurrence risk by 43% (HR 0.57) and improved pathological complete response rates over 5-fold (RR 5.58). Nanotechnology-based delivery systems reduced cardiac toxicity (6% vs. 21%) while maintaining therapeutic efficacy.
Conclusions:
The convergence of precision medicine, AI, robotics, and molecular technologies is revolutionizing cancer surgery toward personalized, data-driven interventions with substantial clinical outcome improvements. Implementation challenges including cost, standardization, and healthcare disparities require systematic addressing for widespread adoption.
Insights
Advancements in precision medicine, AI, and robotics are revolutionizing cancer surgery, leading to improved patient outcomes and personalized treatments. Addressing implementation challenges is key for widespread adoption of these innovative surgical technologies.
Area of Science:
- Oncology
- Surgical Innovation
- Biotechnology
Background:
- Cancer surgery is integrating precision medicine, AI, robotics, advanced imaging, and molecular technologies.
- These innovations aim to enhance surgical precision, improve patient outcomes, and enable personalized, data-driven treatment strategies.
Purpose of the Study:
- To systematically review the clinical applications and outcomes of integrating precision medicine, AI, robotics, and molecular technologies in cancer surgery.
- To analyze therapeutic efficacy, cost-effectiveness, and implementation challenges of these advanced surgical innovations.
Main Methods:
- A systematic literature review was conducted across major databases (PubMed, Embase, Cochrane, Web of Science) from January 2020 to November 2025.
- Studies were analyzed for clinical applications, outcomes, cost-effectiveness, and implementation barriers, focusing on endpoints like surgical accuracy, survival, and complication rates.
Main Results:
- Precision medicine (genomic profiling, ctDNA) shows high sensitivity/specificity for multi-cancer detection.
- AI-assisted surgery improves outcome prediction and reduces complications by 25-30%; robotic surgery enhances precision and reduces tissue damage.
- Fluorescence-guided surgery and perioperative immunotherapy demonstrate significant improvements in survival and recurrence reduction for specific cancers.
Conclusions:
- The integration of precision medicine, AI, robotics, and molecular technologies is transforming cancer surgery towards personalized, data-driven interventions.
- Significant clinical outcome improvements are evident, but challenges like cost and disparities must be addressed for broad implementation.
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