Surgery

Deep learning-based femoral reconstruction from intraoperative point clouds for enhanced knee arthroplasty registration.

PURPOSE: Computer- and robotic-assisted technologies improve total knee arthroplasty (TKA) through intraoperative bone registration. However, limited bone exposure restricts point collection to the distal femur, omitting key geometric features and reducing registration accuracy and the surgical outcomes. METHODS: We introduce a deep learning-based method to improve bone registration by reconstruct...

A novel machine learning approach for prediction of postoperative delirium using multi-domain features of high-density EEG.

Postoperative delirium (POD) poses a significant risk to patients, and accurate prediction of postoperative delirium can provide guidance for positive interventions. Although many studies have applied machine learning (ML) to electronic health records to predict POD, there has been a lack of studies utilizing electroencephalogram (EEG) data to accurately predict POD. Methods: This ret...

A deep learning-based digital biopsy for predicting early recurrence in gastric cancer.

Early postoperative recurrence is a major cause of treatment failure in patients with locally advanced gastric cancer (LAGC), yet current staging syst...

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE) remains a leading cause of early death and profou...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Automated Identification of Cardiopulmonary Disease Cases for Preoperative Risk Stratification Using Machine Learning: A Retrospective Analysis.

BACKGROUND: Preoperative chart review is time-consuming and prone to errors, particularly for cardiopulmonary conditions that impact anesthetic planni...

An algorithm to identify less invasive surfactant administration using a real-world database of preterm infants.

BACKGROUND: Surfactant replacement therapy is central to respiratory distress syndrome (RDS) management in preterm infants, which can be delivered usi...

Micro-CT Evaluation of Robot-Assisted Insertion of CI632 Implant in Human Cadaveric Temporal Bones.

OBJECTIVE: To evaluate the surgical accuracy and intracochlear positioning of robot-assisted insertion of slim modiolar cochlear implant electrode arr...

Bias in Student Evaluations of Surgical Attendings: Role of Gender, Race, Age and Experience.

INTRODUCTION: Student evaluations influence faculty promotion but may reflect implicit bias. We assessed whether surgeon gender, race, age, and experi...

Predicting Postoperative Outcomes in Pediatric Ureteroscopy Using Machine Learning and Explainable AI-EAU Endourology Vision-AI Study.

AIM OF THE STUDY: This study aimed to evaluate the performance of machine learning (ML) algorithms integrated with explainable artificial intelligence...

Deep-learning segmentation to guide bladder neck recognition in robot-assisted radical prostatectomy.

OBJECTIVES: To develop a deep-learning segmentation model for bladder neck dissection during robot-assisted radical prostatectomy (RARP) and evaluate ...

The promise of injectable hydrogels in dental bone regeneration.

Injectable hydrogels are considered to be a minimally invasive approach for the regeneration of the dental bone, providing a number of benefits over t...

Chronic Subdural Hematoma Segmentation: A Dedicated Model to Overcome the Limitations of Acute Hemorrhage Segmentation Across Chronic Subdural Hematoma Subtypes and Density Variations.

Most existing intracranial hematoma segmentation models target acute hemorrhages and may not generalize to the heterogeneous morphology of chronic sub...

AI-based autism identification from hyperspectral imaging detection of oxidative stress in pediatric red blood cells.

BACKGROUND: Oxidative stress (OS) plays a key role in many pathologies, yet the non-invasive, label-free, and cost-effective detection remains a chall...

Hypotension Prediction Index-Guided Hemodynamic Management on Postoperative Organ Outcome: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Intraoperative hypotension (IOH) is a frequent occurrence during noncardiac surgery. Hypotensive episodes can compromise tissue perfusion, and cumulat...

Impact of artificial intelligence-based automated segmentation on the accuracy of robotic computer-aided implant surgery: a retrospective study.

OBJECTIVES: This retrospective study aimed to evaluate the impact of artificial intelligence (AI)-based automated segmentation (AS) on the accuracy of...

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment.

BACKGROUND: Accurate prediction of early recurrence (ER) after radical resection remains a critical challenge in pancreatic ductal adenocarcinoma (PDA...

In-hospital outcomes and cost-effectiveness of transcatheter aortic valve replacement among younger patients: a double/debiased machine learning approach using electronic health records in Germany.

BACKGROUND: The prevalence of severe symptomatic aortic stenosis is increasing with population aging. Although surgical aortic valve replacement (SAVR...

Robotic Pancreaticoduodenectomy with Right Lateral Approach to the Superior Mesenteric Artery: Surgical Artificial Intelligence-Based Visualization for Standardized Dissection.

BACKGROUND: Robotic pancreaticoduodenectomy enables precise vascular dissection, but dissection of the superior mesenteric artery (SMA) remains techni...

Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation.

BACKGROUND: Accurate perioperative risk stratification is essential to patient safety and informed consent in spine surgery. Traditional regression-ba...