Latest AI and machine learning research in surgery for healthcare professionals.
Suction during robotic surgery has traditionally been performed by a bedside assistant. Adequately skilled assistants are not always available. We assessed a purpose-designed robotic surgeon-controlled suction catheter for efficiency and safety by comparing with historic cases of suction controlled by a dedicated bedside assistant using standard rigid laparoscopic suction. Beginning in February ...
BACKGROUND: Few studies have examined robotic surgery from a programmatic standpoint, yet this is how hospitals evaluate return on investment clinically and fiscally. This study examines the 10-year experience of a robotic program at a single academic institution.
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT ang...
BACKGROUND: Machine learning (ML) has garnered increasing attention as a means to quantitatively analyze the growing and complex medical data to impro...
Sensor technologies and data collection practices are changing and improving quality metrics across various domains. Surgical skill assessment in Rob...
BACKGROUND: Venous thoracic outlet syndrome (vTOS) is caused by external compression of the subclavian vein at the costoclavicular junction. It can be...
BACKGROUND: The current standard treatment for external rectal prolapse and symptomatic high-grade internal rectal prolapse is surgical correction wit...
Radical prostatectomy (RP) is the first-line treatment modality for prostate cancer and can be performed using retropubic or minimally invasive techn...
The combination of computing power, connectivity, and big data has been touted as the future of innovation in many fields, including medicine. There h...
Automated machine learning approaches to skin lesion diagnosis from images are approaching dermatologist-level performance. However, current machine l...
Facial recognition has attracted more and more attention since the rapid growth of artificial intelligence (AI) techniques in recent years. However, m...
BACKGROUND: Dividing a surgical procedure into a sequence of identifiable and meaningful steps facilitates intraoperative video data acquisition and s...
Fall detection is a major challenge for researchers. Indeed, a fall can cause injuries such as femoral neck fracture, brain hemorrhage, or skin burns,...
PURPOSE: We aimed to introduce an explainable machine learning technology to help clinicians understand the risk factors for neonatal postoperative mo...
The surgical techniques and devices used to perform radical cystectomy have evolved significantly with the advent of laparoscopic and robotic methods...
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditiona...
OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing ...
The introduction of the intraocular vitrectomy instrument by Machemer et al. has led to remarkable advancements in vitreoretinal surgery enabling the ...