Surgery

Blood loss in one-stage bilateral total knee arthroplasty: cruciate-retaining vs. posterior stabilized. A propensity score-matched analysis.

INTRODUCTION: Although single-stage bilateral total knee arthroplasty (BTKA) presents several advantages, higher perioperative blood loss is a potentiate drawback that is still inevitable. Cruciate retaining (CR) TKA may theoretically result in less blood loss, offer better proprioception, and more physiologic kinematics compared to posterior stabilized (PS) TKA. The objective of this study was to...

A machine learning prediction model for total shoulder arthroplasty procedure duration: an evaluation of surgeon, patient, and shoulder-specific factors.

BACKGROUND: Operating room efficiency is of paramount importance for scheduling, cost efficiency, and to allow for the high operating volume required to address the growing demand for arthroplasty. The purpose of this study was to develop a machine learning predictive model for total shoulder arthroplasty (TSA) procedure duration and to identify factors which are predictive of a prolonged procedur...

Ethics and trustworthiness of artificial intelligence in Hepato-Pancreato-Biliary surgery: a snapshot of insights from the European-African Hepato-Pancreato-Biliary Association (E-AHPBA) survey.

BACKGROUND: Hepato-Pancreato-Biliary (HPB) surgery is a complex specialty and Artificial Intelligence (AI) applications have the potential to improve ...

Predicting Bleeding Related Events in Robotic-Assisted Partial Nephrectomy for Angiomyolipoma: Simplifying Risk Assessment with Tumor Diameter and Depth, A Retrospective Study.

BACKGROUND: Evaluating risk factors for bleeding events in robot-assisted partial nephrectomy (RAPN) for renal angiomyolipoma (RAML) is essential for ...

Assessing the prognostic impact of body composition phenotypes on surgical outcomes and survival in patients with spinal metastasis: a deep learning approach to preoperative CT analysis.

OBJECTIVE: The prognostic significance of body composition phenotypes for survival in patients undergoing surgical intervention for spinal metastases ...

Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies.

Monitoring cerebral oxygenation and metabolism, using a combination of invasive and non-invasive sensors, is vital due to frequent disruptions in hemo...

Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.

INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise an...

Effect of Ultrasound-Guided Extra-Prevertebral Fascial Suprascapular Nerve and Infraclavicular Brachial Plexus Block on Postoperative Analgesia and Phrenic Nerve Function in Shoulder Arthroscopy: A Pilot Study.

PURPOSE: The suprascapular nerve is situated between the prevertebral fascia and the superficial layer of deep cervical fascia and on the surface of t...

Machine learning to predict the decision to perform surgery in hepatic echinococcosis.

BACKGROUND: Cystic echinococcosis (CE) is a significant public health issue, primarily affecting the liver. While several management strategies exist,...

Neuropathology of focal epilepsy: the promise of artificial intelligence and digital Neuropathology 3.0.

Focal lesions of the human neocortex often cause drug-resistant epilepsy, yet ​surgical resection of the epileptogenic region has been proven as a suc...

Augmented Effect of Combined Robotic Assisted Gait Training and Proprioceptive Neuromuscular Facilitation-irradiation Technique on Muscle Activation and Ankle Kinematics in Hemiparetic Gait: A Preliminary Study.

BackgroundProprioceptive neuromuscular facilitation (PNF) alone has limited effectiveness in restoring gait, while robotic-assisted gait training (RAG...

Human Collaborative Control of Lower-Limb Prosthesis Based on Game Theory and Fuzzy Approximation.

For leg prosthesis user, the soft tissue and skin under the stump of are not accustomed to weight bearing, excessive continuous contact pressure can l...

A noninvasive blood glucose detection method with strong time adaptability based on fuzzy operator decision fusion and dynamic spectroscopy characteristics of PPG signals.

PPG signals are a new means of non-invasive detection of blood glucose, but there are still shortcomings of poor time adaptability and low prediction ...

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, but the reasons behind invasion and the changes oc...

Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning.

BACKGROUND: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of ...

Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.

BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accur...

Changes in serum concentration of perioperative inflammatory cytokines following the timing of surgery among mild-moderate traumatic brain injury patients and factors associated.

BACKGROUND: The safe timing window for surgery during the acute phase of inflammation due to traumatic brain injury (TBI) has not been studied extensi...

Stimulated Raman Histology and Artificial Intelligence Provide Near Real-Time Interpretation of Radical Prostatectomy Surgical Margins.

PURPOSE: Balancing surgical margins and functional outcomes is crucial during radical prostatectomy for prostate cancer. Stimulated Raman histology (S...

SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos.

Accurate tool tracking is essential for the success of computer-assisted intervention. Previous efforts often modeled tool trajectories rigidly, overl...

Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis.

OBJECTIVE: This study aims to develop an interpretable machine learning (ML) predictive model to assess its efficacy in predicting postoperative recur...