The current state of artificial intelligence in robotic esophageal surgery

Abstract

Artificial intelligence (AI) is becoming increasingly utilized as a tool for physicians to optimize medical care and patient outcomes. The multifaceted approach to managing esophageal cancer provides a perfect opportunity for machine learning to support clinicians in all stages of management. Preoperatively, AI may aid gastroenterologists and surgeons in diagnosing and prognosticating premalignant or early-stage lesions. Intraoperatively, AI may also aid surgeons in identifying anatomic structures or minimize the learning curve for new learners. Postoperatively, machine learning algorithms can help predict complications and guide high-risk patients through recovery. While still evolving, AI holds promise in enhancing the efficiency and efficacy of multidisciplinary esophageal cancer care.

Keywords

Artificial intelligence / machine learning / neural network / esophagectomy / robotic

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