Latest AI and machine learning research in surgery for healthcare professionals.
Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and interpreting data from clinical trials and research projects to identify subtle but meaningful trends beyond ordinary perception. Artificial intelligence r...
BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to perform a systematic review and meta-analysis to compare the performance of ML vs LR models in predicting postoperative outcomes for patients undergoin...
BACKGROUND: Endoscopic submucosal dissection (ESD) is the standard treatment for early malignant stomach lesions. However, this procedure is technical...
This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding com...
No studies have reported on the impact at team level of the Medtronic Hugo RAS system. We described the work patterns and learning curves of an experi...
Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The Cytosponge-...
BACKGROUND: Pre-operative risk assessment can help clinicians prepare patients for surgery, reducing the risk of perioperative complications, length o...
This study aimed to investigate the minimum number of operations required for itinerant nurses in the operating room to master the skills needed to op...
PURPOSE: Given the limitations of extant models for normal tissue complication probability estimation for osteoradionecrosis (ORN) of the mandible, th...
Steady-state visual evoked potential (SSVEP) is a key technique of electroencephalography (EEG)-based brain-computer interfaces (BCI), which has been ...
This study aimed to assess the effectiveness and safety of robot-assisted versus fluoroscopy-assisted pedicle screw implantation in scoliosis surgery....
OCCUPATIONAL APPLICATIONSWe used a survey to evaluate the perceptions of nurses and nursing students on robotic technology for nursing care before and...
New robot-assisted surgery platforms being developed will be required to have proficiency-based simulation training available. Scoring methodologies a...
Proper codification of medical diagnoses and procedures is essential for optimized health care management, quality improvement, research, and reimburs...
BACKGROUND: The landscape of robotic surgery is evolving with the emergence of new platforms. However, reports on their applicability in different sur...
Digital surgery technologies, such as interventional robotics and sensor systems, not only improve patient care but also aid in the development and op...
A companion robot named Hyodol is a digital technology implemented for eldercare in South Korea. Drawing insights from semi-structured interviews with...
At the central workplace of the surgeon the digitalization of the operating room has particular consequences for the surgical work. Starting with intr...
BACKGROUND: Endoscopic full-thickness gastric resection (EFTGR) with regional lymph node dissection (LND) has been used for early gastric cancer (EGC)...
This meta-analysis aims to evaluate the safety and oncological outcomes of robotic surgery compared to open surgery in treating gallbladder cancer (GB...