Surgery

Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, subdural, epidural, and subarachnoid) in non-contrast head CT.

Embolizing intracranial arteriovenous malformations with Onyx: experience at a single center with 250 patients.

The aim of this study is to evaluate the embolization techniques, as well as the effects and complications, using the non-adhesive liquid embolic material Onyx in intracranial arteriovenous malformations (AVMs). The study comprises a retrospective analysis of 250 patients with intracranial AVMs treated with Onyx in Guangdong General Hospital from Jan 2010 to Dec 2017. The therapeutic strategies,...

Segmenting and classifying activities in robot-assisted surgery with recurrent neural networks.

PURPOSE: Automatically segmenting and classifying surgical activities is an important prerequisite to providing automated, targeted assessment and fee...

Single position spinal surgery for the treatment of grade II spondylolisthesis: A technical note.

BACKGROUND AND IMPORTANCE: Minimally invasive transpsoas approach to treat lumbar spondylolisthesis is associated with increased clinical benefits.

A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping.

Although robotic telemanipulation has always been a key technology for the nuclear industry, little advancement has been seen over the last decades. D...

Emergence of behavior through morphology: a case study on an octopus inspired manipulator.

The complex motion abilities of the Octopus vulgaris have been an intriguing research topic for biologists and roboticists alike. Various studies have...

Development of a robotic walker for individuals with cerebral palsy.

This study describes the first use of a robotic walker in youth and young adults with cerebral palsy (CP) Gross Motor Function Classification (GMFCS)...

Using Surgeon Hand Motions to Predict Surgical Maneuvers.

OBJECTIVE: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical bencht...

Accuracy of American College of Surgeons National Surgical Quality Improvement Program Universal Surgical Risk Calculator in Predicting Complications Following Robot-Assisted Radical Cystectomy at a National Comprehensive Cancer Center.

There is paucity of literature about the validation of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) sur...

Qualification of a chemotherapy-compounding robot.

KIRO® Oncology (Kiro Grifols, Spain) is a robotic system for automated compounding of sterile injectable drugs including intravenous cytotoxic treatme...

Learning soft tissue behavior of organs for surgical navigation with convolutional neural networks.

PURPOSE: In surgical navigation, pre-operative organ models are presented to surgeons during the intervention to help them in efficiently finding thei...

Machine Learning Analysis of Matricellular Proteins and Clinical Variables for Early Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Although delayed cerebral ischemia (DCI) is a well-known complication after subarachnoid hemorrhage (SAH), there are no reliable biomarkers to predict...

Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy.

Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraope...

Re: Health Economic Analysis of Open and Robot-assisted Laparoscopic Surgery for Prostate Cancer Within the Prospective Multicentre LAPPRO Trial.

Active learning using deep Bayesian networks for surgical workflow analysis.

PURPOSE: For many applications in the field of computer-assisted surgery, such as providing the position of a tumor, specifying the most probable tool...

Weakly supervised convolutional LSTM approach for tool tracking in laparoscopic videos.

PURPOSE: Real-time surgical tool tracking is a core component of the future intelligent operating room (OR), because it is highly instrumental to anal...

Efficient Corrections for DFT Noncovalent Interactions Based on Ensemble Learning Models.

Machine learning has exhibited powerful capabilities in many areas. However, machine learning models are mostly database dependent, requiring a new mo...

Improving Outcomes Defending Patient Safety: The Learning Journey in Robotic Liver Resections.

BACKGROUND: While laparoscopy is currently adopted for hepatic resections, robotic approaches to the liver have not gained wide acceptance. We decided...

Robot-Assisted Simple Prostatectomy: Illustration of a Simplified Extraperitoneal Transcapsular Technique.

Robot-assisted simple prostatectomy (RASP) performed with the extraperitoneal (EP) technique (RASP-EP) minimizes the risk of bowel injury, particular...

Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the...