Surgery

Head-down tilt lithotomy position and well-leg compartment syndrome: An international survey of current practice.

AIM: Well-leg compartment syndrome (WLCS) is a serious complication of prolonged surgery in the head-down tilt lithotomy (HDTL) position associated with increased postoperative morbidity and mortality. However, there is a lack of awareness and clinical guidance regarding prevention of WLCS. The aim of this study was to assess current HDTL-related practices and occurrence of WLCS among a global coh...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative surgical variables - including clamping strategy, resection technique, and renorrhaphy type - to estimate the 3-month postoperative eGFR drop. A Rando...

An overview of artificial intelligence and machine learning in shoulder surgery.

Machine learning (ML), a subset of artificial intelligence (AI), utilizes advanced algorithms to learn patterns from data, enabling accurate predictio...

Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study.

BACKGROUND AND AIMS: Surgical repair of femoral shaft fractures continues to have notable perioperative morbidity and mortality. The purpose of this s...

The legal and ethical considerations in cross-border telesurgical procedures.

Telesurgery, or remote surgery, represents a transformative fusion of medicine and technology, enabling surgeons to perform procedures on patients loc...

A multi-model deep learning approach for the identification of coronary artery calcifications within 2D coronary angiography images.

PURPOSE: Identifying and quantifying coronary artery calcification (CAC) is crucial for preoperative planning, as it helps to estimate both the comple...

Deep Learning Algorithms to Predict Differential Renal Function <40% in Unilateral Hydronephrosis Based on Key Parameters of Urinary Tract Ultrasound.

OBJECTIVE: To identify the correlation between ultrasound findings and the incidence of differential renal function (DRF) <40%, we conducted an analys...

Cutting Skill Assessment by Motion Analysis Using Deep Learning and Spatial Marker Tracking.

The assessment of surgical skill is crucial for indicating a surgeon's proficiency. While motion analysis of surgical tools is widely used in endoscop...

Machine learning in risk assessment for microvascular head and neck surgery.

PURPOSE: The integration of machine learning (ML) into microvascular surgery for the head and neck offers significant potential to enhance risk strati...

Fast Virtual Stenting for Thoracic Endovascular Aortic Repair of Aortic Dissection Using Graph Deep Learning.

Fast virtual stenting (FVS) is a promising preoperative planning aid for thoracic endovascular aortic repair (TEVAR) of aortic dissection. It aims at ...

Deep learning based on ultrasound images predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma.

OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for predicting cervical lymph node metastasis (CLNM) ...

Patient reported outcome measures: from the classics to AI.

With its basis in the development of intelligence testing, classical test theory paved the way to develop patient-reported outcome measures - tools ca...

Alpha test 1 robotic platform for traditional Chinese medicine pretreatment: Automated modular integration and quality control applications.

Sample pretreatment plays an important role in analytical performance, but it is often the rate-limiting step in scientific research. With the develop...

Large language models in breast cancer reconstruction: A framework for patient-specific recovery and predictive insights.

Breast cancer reconstruction, a vital part of comprehensive cancer therapy, can be performed concurrently with cancer resection, improving both physic...

Artificial intelligence medical image-aided diagnosis system for risk assessment of adjacent segment degeneration after lumbar fusion surgery.

The existing assessment of adjacent segment degeneration (ASD) risk after lumbar fusion surgery focuses on a single type of clinical information or im...

Artificial intelligence classifies surgical technical skills in simulated laparoscopy: a pilot study.

OBJECTIVE: To develop a computer algorithm for the automatic classification of basic surgical skills in laparoscopy. The ability to objectively assess...

Deep Learning to Localize Photoacoustic Sources in Three Dimensions: Theory and Implementation.

Surgical tool tip localization and tracking are essential components of surgical and interventional procedures. The cross sections of tool tips can be...

Deep learning-based intraoperative visual guidance model for ureter identification in laparoscopic sigmoidectomy.

BACKGROUND: Identifying the left ureter is a key step while performing laparoscopic sigmoid resection to prevent intraoperative injury and postoperati...

MEF-Net: Multi-scale and edge feature fusion network for intracranial hemorrhage segmentation in CT images.

Intracranial Hemorrhage (ICH) refers to cerebral bleeding resulting from ruptured blood vessels within the brain. Delayed and inaccurate diagnosis and...

Predicting Severe Postoperative Complications after CRS-HIPEC: An Externally Validated Machine-Learning Tool.

INTRODUCTION: Current decision support tools designed to predict postoperative complications, following cytoreductive surgery with hyperthermic intrap...