Latest AI and machine learning research in surgery for healthcare professionals.
In this work, a novel semisupervised framework is proposed to tackle the small-sample problem of dental-based human identification (DHI), achieving enhanced performance via a "classifying while generating" paradigm. A generative adversarial network (GAN), called the DHI-GAN, is presented to implement this idea, in which an extra classifier is also dedicatedly proposed to achieve an efficient train...
Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, there are few techniques to model PCI skill so far. In this study, a learning framework with local and ensemble learning is proposed to learn skill characteristics of different skill-level subjects from...
INTRODUCTION: Robot-assisted navigation bronchoscopy (RANB) has been gaining traction as a new technology for minimally invasive biopsies of periphera...
The potential applications of artificial intelligence (AI) in health care have garnered significant interest in recent years. This study presents the ...
INTRODUCTION: The Medtronic Hugo™ Robot-assisted Surgery (RAS) system was recently approved for clinical use. We explored the safety and feasibility o...
BACKGROUND: It is unknown whether the da Vinci single-port system performs similarly to the previous multi-port system during complicated procedures, ...
This article presents a systematic review on wearable robotic devices that use human-in-the-loop optimization (HILO) strategies to improve human-robot...
Type-b aortic dissection (AD) is a life-threatening cardiovascular disease and the primary treatment is thoracic endovascular aortic repair (TEVAR). D...
Accurately predicting functional outcomes in patients with spinal cord injury (SCI) helps clinicians set realistic functional recovery goals and impro...
BACKGROUND: Robot-assisted radical prostatectomy is a minimally invasive, safe procedure preferred in the management of localized prostate cancer. In ...
OBJECTIVE: The primary aim of this research was to harness the capabilities of deep learning to enhance neurosurgical procedures, focusing on accurate...
BACKGROUND: Learning curve, training, and cost impede widespread implementation of new technology. Neurosurgical robotic technology introduces challen...
For more than 2 decades since the first imaging procedure was performed in a living patient, intravascular optical coherence tomography (OCT), with it...
BACKGROUND: The KangDuo-Surgical Robot-01 (KD-SR-01) system is a new surgical robot recently developed in China. The aim of this study was to present ...
BACKGROUND: Endoluminal surgery is increasingly recognized as a mode of treatment for colorectal neoplasms with the latest robotic single port platfor...
BACKGROUND: This study aimed to evaluate the risk factors for machine learning (ML) algorithms in predicting postoperative surgical site infection (SS...
Coral reef atherosclerosis of the paravisceral aorta is a rare disease whose description is confined to before contemporary vascular surgical techniqu...
Fetoscopic Laser Coagulation (FLC) for Twin to Twin Transfusion Syndrome is a challenging intervention due to the working conditions: low quality imag...
BACKGROUND/AIM: Surfactant is a surface-active substance that, in addition to its detergent effect, also has effects that reduce inflammation and fibr...
OBJECTIVE: The role of surgery in spontaneous intracerebral hemorrhage (SICH) remains controversial. We aimed to use explainable machine learning (ML)...