Surgery

Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit.

BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to build, streamline, temporally validate, and use ML models for prediction of PCNL outcomes (intensive care admission, postoperative infection, transfusio...

Robot-assisted versus laparoscopic pheochromocytoma resection and construction of a nomogram to predict perioperative hemodynamic instability.

BACKGROUND: Despite recent improvements in perioperative outcomes after pheochromocytoma resection, hemodynamic instability (HI) remained of high concern. The emergence of robot-assisted surgery may bring different results to pheochromocytoma surgery. The purposes of this study were to investigate whether robot-assisted retroperitoneal pheochromocytoma resection promotes hemodynamic instability co...

Preliminary report on a novel technique for endoscopic transaxillary thyroidectomy: a case-control study.

BACKGROUND: Endoscopic transaxillary approaches to thyroidectomy have been well described and gasless transaxillary endoscopic thyroidectomy (GTET) is...

A Deep Learning-Based Platform for Workers' Stress Detection Using Minimally Intrusive Multisensory Devices.

The advent of Industry 4.0 necessitates substantial interaction between humans and machines, presenting new challenges when it comes to evaluating the...

Robotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination.

Gait coordination (GC), meaning that one leg moves in the same pattern but with a specific phase lag to the other, is a spontaneous behavior in the wa...

CT angiography prior to endovascular procedures: can artificial intelligence improve reporting?

CT angiography prior to endovascular aortic surgery is the standard non-invasive imaging method for evaluation of aortic dimensions and access sites. ...

Automated deep learning model for estimating intraoperative blood loss using gauze images.

The intraoperative estimated blood loss (EBL), an essential parameter for perioperative management, has been evaluated by manually weighing blood in g...

Deep-learning model to improve histological grading and predict upstaging of atypical ductal hyperplasia / ductal carcinoma in situ on breast biopsy.

AIMS: Risk stratification of atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS), diagnosed using breast biopsy, has great clinical ...

Impact of visceral fat area on short-term outcomes in robotic surgery for mid and low rectal cancer.

Rectal cancer is one of the most prevalent cancers that arise in the digestive tract. The purpose of this retrospective study was to investigate the i...

Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases.

BACKGROUND: Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This st...

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of art...

Deep learning-based white matter lesion volume on CT is associated with outcome after acute ischemic stroke.

BACKGROUND: Intravenous thrombolysis (IVT) before endovascular treatment (EVT) for acute ischemic stroke might induce intracerebral hemorrhages which ...

Surgical phase and instrument recognition: how to identify appropriate dataset splits.

PURPOSE: Machine learning approaches can only be reliably evaluated if training, validation, and test data splits are representative and not affected ...

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation.

OBJECTIVE: Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience lev...

Outcomes of robot-assisted laparoscopic extended pelvic lymph node dissection for prostate Cancer.

INTRODUCTION: Extended pelvic lymph node dissection (ePLND) in men undergoing robot-assisted laparoscopic radical prostatectomy (RARP) is a widely use...

Robotic transanal minimally invasive surgery for the regrowth of rectal cancer following a watch-and-wait approach - a video vignette.

Validate robot-assisted total laparoscopic hysterectomy with four equally-spaced ports without an assistant port.

To evaluate the usefulness of robot-assisted total laparoscopic hysterectomy with four equally-spaced ports (RA-TLH/4e) without an assistant port. In ...

The influence of the da Vinci surgical robot on electromagnetic tracking in a clinical environment.

Robot-assisted surgery is increasingly used in surgery for cancer. Reduced overview and loss of anatomical orientation are challenges that might be so...

Conception and prospective multicentric validation of a Robotic Surgery Training Curriculum (RoSTraC) for surgical residents: from simulation via laboratory training to integration into the operation room.

There is a lack of training curricula and educational concepts for robotic-assisted surgery (RAS). It remains unclear how surgical residents can be tr...

Transferability of the robot assisted and laparoscopic suturing learning curves.

Robot assisted surgery (RAS) is increasingly used, and besides conventional minimally invasive surgery (cMIS) surgeons are challenged to learn an incr...