Latest AI and machine learning research in surgery for healthcare professionals.
Deep learning has become a research hotspot in multimedia, especially in the field of image processing. Pooling operation is an important operation in deep learning. Pooling operation can reduce the feature dimension, the number of parameters, the complexity of computation, and the complexity of time. With the development of deep learning models, pooling operation has made great progress. The main...
Patient-reported outcomes (PROs) enable providers to identify differences in treatment effectiveness, postoperative recovery, quality of life, and patient satisfaction. By allowing a shift from disease-specific factors to the patient perspective, PROs provide a tailored patient-centric approach to shared decision-making. Artificial intelligence (AI) and machine learning (ML) techniques can facilit...
In industrial processes, different operating conditions and ratios of ingredients are used to produce multi-grade products in the same production line...
Artificial intelligence (AI) has made steady in-roads into the healthcare scenario over the last decade. While widespread adoption into clinical pract...
The goal of this study was to quantify and compare prospective self-reported intraoperative workload and teamwork during robot-assisted radical prosta...
Robotic hands have long strived to reach the performance of human hands. The physical complexity and extraordinary capabilities of the human hand, in ...
BACKGROUND: In recent years, the robot surgical system begins to be applied in single-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-...
OBJECTIVE: To determine whether proficiency-based progression (PBP) training leads to better robotic surgical performance compared to traditional trai...
PURPOSE: Evidence regarding local recurrence rates in the initial cases after implementation of robot-assisted total mesorectal excision is limited. T...
Robot-assisted systems offer great potential for gentler and more precise cochlear implantation. In this article, we provide a comprehensive overview ...
OBJECTIVE: Application effect of Leonardo's robot-assisted laparoscopy in hepatectomy for colorectal cancer patients with liver metastases.
Colorectal cancer (CRC) is the third most common cancer worldwide. Although clinical outcome varies among patients diagnosed within the same TNM stage...
Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to est...
INTRODUCTION: Warm ischemia time (WIT) is a primary concern for robot-assisted laparoscopic partial nephrectomy (RALPN) patients because longer WIT is...
Machine-learning based risk prediction models have the potential to improve patient outcomes by assessing risk more accurately than clinicians. Signif...
BACKGROUND: Robot-assisted sleeve gastrectomy (RSG) is an increasingly common approach to sleeve gastrectomy (SG). Staple line reinforcement (SLR) is ...
INTRODUCTION: Robotic surgery is a method of minimally invasive surgery performed through small incisions using a remote robotic console. Surgical res...
Wireless millimeter-scale origami robots have recently been explored with great potential for biomedical applications. Existing millimeter-scale origa...
BACKGROUND: The standard treatment of rectal carcinoma is surgical resection according to the total mesorectal excision principle, either by open, lap...
OBJECTIVES: Transoral robotic surgery in adults confers excellent results and decreased morbidity. Application of these techniques has not yet been ri...