Surgery

Deep learning-based hemorrhage detection for diabetic retinopathy screening.

Diabetic retinopathy is a retinal compilation that causes visual impairment. Hemorrhage is one of the pathological symptoms of diabetic retinopathy that emerges during disease development. Therefore, hemorrhage detection reveals the presence of diabetic retinopathy in the early phase. Diagnosing the disease in its initial stage is crucial to adopt proper treatment so the repercussions can be preve...

Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis-Review of literature and in vitro case study.

The digital health industry is experiencing fast-paced research which can provide digital care programs and technologies to enhance the competence of healthcare delivery. Orthopedic literature also confirms the applicability of artificial intelligence (AI) and machine learning (ML) models to medical diagnosis and clinical decision-making. However, implant monitoring after primary surgery often hap...

Pediatric robotic surgery: An overview.

Pediatric robotic surgery offers children a minimally invasive approach with numerous advantages over open or thoracoscopic and laparoscopic surgery. ...

Robotic-assisted minimally invasive surgery: Foregut procedures in pediatric patients.

Utilization of robotics in pediatric surgical oncology.

Despite increasing implementation of robotic surgery and minimally invasive techniques within adult surgical oncology and pediatric general surgery, t...

Early recognition of risk of critical adverse events based on deep neural decision gradient boosting.

INTRODUCTION: Perioperative critical events will affect the quality of medical services and threaten the safety of patients. Using scientific methods ...

Robot-assisted laparoscopic cystectomy with non-continent urinary diversion for neurogenic lower urinary tract dysfunction: Midterm outcomes.

OBJECTIVES: The aim of this study was to assess midterm functional outcomes and complications of robot-assisted laparoscopic cystectomy with non-conti...

Prediction of malignancy upgrade rate in high-risk breast lesions using an artificial intelligence model: a retrospective study.

PURPOSE: High-risk breast lesions (HRLs) are associated with future risk of breast cancer. Considering the pathological subtypes, malignancy upgrade r...

Adverse Events and Morbidity in a Multidisciplinary Pediatric Robotic Surgery Program. A prospective, Observational Study.

OBJECTIVE: To report one-year morbidity of robotic-assisted laparoscopic surgery (RALS) in a dedicated, multidisciplinary, pediatric robotic surgery p...

Robotic pelvic side-wall lymph node dissection for rectal cancer: a systematic review of videos and application of the IDEAL 2A framework.

Lateral pelvic lymph node dissection (LPLND) in rectal cancer has gained increasing traction worldwide. Robotic LPLND is an emerging technique. Utilis...

Objective assessment of intraoperative skills for robot-assisted partial nephrectomy (RAPN).

RAPN training usually takes place in-vivo and methods vary across countries/institutions. No common system exists to objectively assess trainee capaci...

Development of a remote-control system for catheterization capable of high-speed force feedback.

PURPOSE: There is a growing interest in minimally invasive surgery as interventional radiology (IVR), which decreases the burden on a patient. However...

[Robotic versus laparoscopic rectal resection : Results of a randomized trial].

Robot-assisted versus conventional laparoscopic radical hysterectomy in cervical cancer stage IB1.

The aim of this study was to compare survival outcomes of robot-assisted laparoscopic radical hysterectomy (RRH) and conventional laparoscopic radica...

Outcomes of Robot-assisted Radical Prostatectomy with the Hugo RAS Surgical System: Initial Experience at a High-volume Robotic Center.

Clinical data on robot-assisted radical prostatectomy (RARP) performed with the new Hugo robot-assisted surgery (RAS) system are scarce. We described ...

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks.

Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, preoperative risk-reduction, and postoperative res...

The Surgical Learning Curve: Does Robotic Technical Skill Explain Differences in Operative Performance?

Prior studies on technical skills use small collections of videos for assessment. However, there is likely heterogeneity of performance among surgeon...

FUN-SIS: A Fully UNsupervised approach for Surgical Instrument Segmentation.

Automatic surgical instrument segmentation of endoscopic images is a crucial building block of many computer-assistance applications for minimally inv...

State-of-the-art Applications of Patient-Reported Outcome Measures in Spinal Care.

Patient-reported outcome measures (PROMs) assign objective measures to patient's subjective experiences of health, pain, disability, function, and qua...

Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images.

PURPOSE: We analyzed clinical features and the representative HE-stained pathologic images to predict 5-year overall survival via the deep-learning ap...