Year: 2025
Type: article
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.
Source: Mini-invasive Surgery
Authors: Constantine M. Poulos, Ryan Cassidy, Eamon Khatibifar, Erik Holzwanger, Lana Schumacher
Institutions: Tufts Medical Center, Tufts University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Tufts Medical Center
OpenAlex ID: W4407420504