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Archives of Surgical Oncology

ISSN: 2471-2671

Open Access

Advances in Surgical Phase Recognition: Overcoming Challenges in Structure Segmentation for Rectal Resection Videos

Abstract

Simon Jones*

In the ever-evolving landscape of healthcare, technology has emerged as a powerful catalyst for enhancing the precision and efficacy of medical procedures. One field where this transformation is particularly noteworthy is rectal surgery. This article explores the promising realm of machine learning applied to phase and structure recognition in rectal surgery, shedding light on the significant strides being made in surgical phase recognition within rectal resection videos. We embark on a journey through the convergence of technology and surgical excellence, showcasing how machine learning, a subset of artificial intelligence, is reshaping the practice of medicine. With its capability to analyze vast datasets, identify intricate patterns, and make insightful predictions, machine learning stands as a transformative force in the world of rectal surgery, promising a future marked by heightened precision and improved patient outcomes.

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