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Neoplasm Recurrence, Local

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Prediction of biochemical recurrence after robot-assisted radical prostatectomy: analysis of 784 Japanese patients.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To examine biochemical recurrence after robot-assisted radical prostatectomy in Japanese patients, and to develop a risk stratification model for biochemical recurrence.

Robotic versus laparoscopic intersphincteric resection for low rectal cancer: comparison of the operative, oncological, and functional outcomes.

Annals of surgical oncology
BACKGROUND: Robotic surgery was developed to overcome the limitations of laparoscopic surgery and is increasingly used to treat low rectal cancer. In this study, we compared the operative, oncological, and functional outcomes of low rectal cancer pat...

A systematic review and meta-analysis evaluating completeness and outcomes of robotic thyroidectomy.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: Despite immense interest, robotic-assisted thyroidectomy (RT) remains controversial in differentiated thyroid carcinoma (DTC). This systematic review and meta-analysis compared surgical completeness and/or oncological outcomes ...

Artificial intelligence in liver cancer surgery: Predicting success before the first incision.

World journal of gastroenterology
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang , which presents a recent multicenter cohort study demonstrated that machine learning algorithms effectively strati...

Validation of a Digital Pathology-Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate cancer treated with definitive radiation, using biopsy digital pathology images and key clinical in...

Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection.

World journal of gastroenterology
BACKGROUND: Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy pro...

Predicting early recurrence of hepatocellular carcinoma after thermal ablation based on longitudinal MRI with a deep learning approach.

The oncologist
BACKGROUND: Accurate prediction of early recurrence (ER) is essential to improve the prognosis of patients with hepatocellular carcinoma (HCC) underwent thermal ablation (TA). Therefore, a deep learning model system using longitudinal magnetic resona...

Leveraging Artificial Intelligence and Radiomics for Improved Nasopharyngeal Carcinoma Prognostication.

Cancer medicine
INTRODUCTION: Nasopharyngeal carcinoma (NPC) typically presents as advanced disease due to the lack of significant symptoms in the early stages. Accurate prognostication is therefore challenging as current methods based on anatomical staging often la...

Machine learning model using immune indicators to predict outcomes in early liver cancer.

World journal of gastroenterology
BACKGROUND: Patients with early-stage hepatocellular carcinoma (HCC) generally have good survival rates following surgical resection. However, a subset of these patients experience recurrence within five years post-surgery.