Latest AI and machine learning research in surgery for healthcare professionals.
An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical ...
OBJECTIVE: The analysis of surgical videos using artificial intelligence holds great promise for the future of surgery by facilitating the development of surgical best practices, identifying key pitfalls, enhancing situational awareness, and disseminating that information via real-time, intraoperative decision-making. The objective of the present study was to examine the feasibility and accuracy o...
The advent of AI in surgical practice is representing a major innovation. As its role expands and due to its several implications, strict compliance w...
PURPOSE: Transoral robotic surgery is well established in the treatment paradigm of oropharyngeal pathology. The Versius Surgical System (CMR Surgical...
Artificial intelligence (AI) has witnessed significant advancements, reshaping various industries, including healthcare. The introduction of ChatGPT b...
Soft actuators capable of remote-controlled guidance and manipulation within complex constrained spaces hold great promise in various fields, especial...
BACKGROUND: Consolidative resection or cytoreductive radical prostatectomy (CRP) may benefit men with non-organ confined prostate cancer. We report th...
BACKGROUND: To demonstrate the effectiveness and feasibility of robotic portal resection (RPR) for mediastinal tumour using a prospectively collected ...
BACKGROUND: Aimed to assess clinical effect of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection by comparing ...
We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learnin...
BACKGROUND: The formulation of clinical recommendations pertaining to bariatric surgery is essential in guiding healthcare professionals. However, the...
Several studies reported that20% of patients were unhappy with the outcome of their total knee arthroplasty (TKA). Having commenced robot assist TKA w...
PURPOSE: Patients are using online search modalities to learn about their eye health. While Google remains the most popular search engine, the use of ...
Robotic-assisted surgery has gained momentum in the pursuit of improved minimally invasive procedures. The adoption of new robotic platforms, such as ...
This study aims to propose a generative deep learning model (GDLM) based on a variational autoencoder that predicts macular optical coherence tomograp...
Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectom...
Cell mechanotransduction signals are important targets for physical therapy. However, current physiotherapy heavily relies on ultrasound, which is gen...
BACKGROUND: Robot-assisted radical prostatectomy (RARP) with extended lymphadenectomy (ePLND) is the gold standard for surgical treatment of prostate ...
Various complications can occur during robot-assisted thoracic surgery for mediastinal tumors owing to carbon dioxide (CO2) insufflation. This study r...