Surgery

Clinical efficiency of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection.

BACKGROUND: Aimed to assess clinical effect of three-port inflatable robot-assisted thoracoscopic su...

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

We constructed an early prediction model for postoperative pulmonary complications after thoracoscop...

Is 80% satisfaction still the expectation in modern TKA mechanically aligned with robot assist? We think not.

Several studies reported that20% of patients were unhappy with the outcome of their total knee arthr...

Dr. Google vs. Dr. ChatGPT: Exploring the Use of Artificial Intelligence in Ophthalmology by Comparing the Accuracy, Safety, and Readability of Responses to Frequently Asked Patient Questions Regarding Cataracts and Cataract Surgery.

PURPOSE: Patients are using online search modalities to learn about their eye health. While Google r...

Operative efficiency: a comparative analysis of Versius and da Vinci robotic systems in abdominal surgery.

Robotic-assisted surgery has gained momentum in the pursuit of improved minimally invasive procedure...

Accuracy of generative deep learning model for macular anatomy prediction from optical coherence tomography images in macular hole surgery.

This study aims to propose a generative deep learning model (GDLM) based on a variational autoencode...

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy.

Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabi...

Robotic TAMIS rectal neuroendocrine tumor excision.

Extended pelvic lymph node dissection during robotic prostatectomy: antegrade versus retrograde technique.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) with extended lymphadenectomy (ePLND) is the...

Cardiac Tamponade Caused By Carbon Dioxide Insufflation During Robot-Assisted Thoracic Surgery: A Case Report.

Various complications can occur during robot-assisted thoracic surgery for mediastinal tumors owing ...

Development of a Machine Learning Model to Predict the Use of Surgery in Patients With Rheumatoid Arthritis.

OBJECTIVE: One in five patients with rheumatoid arthritis (RA) rely on surgery to restore joint func...

Technical and functional design considerations for a real-world interpretable AI solution for NIR perfusion analysis (including cancer).

Near infrared (NIR) analysis of tissue perfusion via indocyanine green fluorescence assessment is pe...

Use of artificial intelligence in the detection of the critical view of safety during laparoscopic cholecystectomy.

BACKGROUND: This study aimed to evaluate the use of artificial intelligence (AI) to detect the criti...

hinotori vs. da Vinci: propensity score-matched analysis of surgical outcomes of robot-assisted radical prostatectomy.

hinotori™ is a recently developed surgical robot system. The present study aims to compare intraoper...

Comparison of the S8 navigation system and the TINAVI orthopaedic robot in the treatment of upper cervical instability.

The objective is to compare the clinical efficacy and safety of the S8 navigation system and the Tin...

Deep Learning-Based Multi-Class Segmentation of the Paranasal Sinuses of Sinusitis Patients Based on Computed Tomographic Images.

Accurate paranasal sinus segmentation is essential for reducing surgical complications through surgi...

Implementation of single-port robotic urologic surgery: experience at a large academic center.

The Single-Port (SP) robotic system is increasingly being implemented in the United States, allowing...

Effect of different targets of goal-directed fluid therapy on intraoperative hypotension and fluid infusion in robot-assisted laparoscopic gynecological surgery: a randomized non-inferiority trial.

Carotid corrected flow time (FTc) and tidal volume challenge pulse pressure variation (VtPPV) are us...

A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma.

This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung ad...

The development of a deep learning model for automated segmentation of the robotic pancreaticojejunostomy.

BACKGROUND: Minimally invasive surgery provides an unprecedented opportunity to review video for ass...

A Pilot Study Using Machine-learning Algorithms and Wearable Technology for the Early Detection of Postoperative Complications After Cardiothoracic Surgery.

OBJECTIVE: To evaluate whether a machine-learning algorithm (ie, the "NightSignal" algorithm) can be...