Development of Artificial Intelligence for Parathyroid Recognition During Endoscopic Thyroid Surgery.

Objective: We aimed to establish an artificial intelligence (AI) model to identify parathyroid glands during endoscopic approaches and compare it with senior and junior surgeons' visual estimation.

Methods: A total of 1,700 images of parathyroid glands from 166 endoscopic thyroidectomy videos were labeled. Data from 20 additional full-length videos were used as an independent external cohort.

Nomogram for prognosis of patients with esophageal squamous cell cancer after minimally invasive esophagectomy established based on non-textbook outcome.

Background: Non-textbook outcome (non-TO) represents a new prognostic evaluation index for surgical oncology. The present study aimed to develop new nomograms based on non-TO to predict the mortality and recurrence rate in patients with esophageal squamous cell cancer (ESCC) after minimally invasive esophagectomy (MIE).

Methods: The study involved a retrospective analysis of 613 ESCC patients, from the prospectively maintained database from January 2011 to December 2018.

Textbook outcome after minimally invasive esophagectomy is an important prognostic indicator for predicting long-term oncological outcomes with locally advanced esophageal squamous cell carcinoma.

Background: The textbook outcome (TO) emerges as a novel prognostic factor in surgical oncology. The present study aimed to evaluate the effect of TO on the risk of death and recurrence in patients with esophageal squamous cell carcinoma (ESCC) after minimally invasive esophagectomy (MIE).

Methods: The study involved retrospective analysis of 528 patients with ESCC who were subjected to MIE from January 2011 to December 2017.