Surgery

The role of phenotypic age acceleration in aneurysmal subarachnoid hemorrhage: analysis of retrospective data from two hospital-based cohorts and prospective UK Biobank cohort.

BACKGROUND: Phenotypic age acceleration (PhenoAgeAccel) is considered a major risk factor for various age-related diseases, but its specific role in aneurysmal subarachnoid hemorrhage (aSAH) remains unclear. This study aims to examine the relationship between PhenoAgeAccel and the risk of aSAH, and further explores whether genetic susceptibility modifies this association.

Transforming healthcare: the impact of artificial intelligence on diagnostics, pharmaceuticals and ethical considerations - a comprehensive review.

Interpretability of results remains challenging in most health industries since patients may suffer life-threatening consequences from an inaccurate diagnosis. Artificial Intelligence (AI) integration has arisen as a prominent technology in the healthcare sector, transforming the field by advancing early diagnostics, surgeries, and ethical concerns. The present review analyses the multidimensional...

Deep learning-based radiomics and machine learning for prognostic assessment in IDH-wildtype glioblastoma after maximal safe surgical resection: a multicenter study.

BACKGROUND: Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis. This study aimed to construct and validate a radiomics-based ma...

Optimization of an artificial neural network for predicting stress in robot-assisted laparoscopic surgery based on EDA sensor data.

PURPOSE: This study aims to optimize tunable hyperparameters of the multilayer perceptron (MLP) setup. The optimization procedure is aimed at more acc...

Artificial Intelligence and Musculoskeletal Surgical Applications.

Artificial intelligence (AI) has emerged as a transformative force in orthopedic surgery. Potentially encompassing pre-, intra-, and postoperative pro...

Delirium in Critically Ill Geriatric Surgical Patients: A Systematic Review of Screening, Risk Factors, Diagnosis, and Management.

OBJECTIVE: This systematic review aims to evaluate optimal early screening strategies, significant risk factors, and effective diagnostic and manageme...

Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review.

The aim of this study was to show the efficacy described in the scientific literature of lung ultrasound (LU) during video-assisted thoracic surgery (...

Risk prediction of stroke-associated pneumonia in acute ischemic stroke with atrial fibrillation using machine learning models.

Stroke-associated pneumonia (SAP) is a serious complication of acute ischemic stroke (AIS), significantly affecting patient prognosis and increasing h...

Predicting alveolar nerve injury and the difficulty level of extraction impacted third molars: a systematic review of deep learning approaches.

BACKGROUND: Third molar extraction, a common dental procedure, often involves complications, such as alveolar nerve injury. Accurate preoperative asse...

Convolutional autoencoder-based deep learning for intracerebral hemorrhage classification using brain CT images.

Intracerebral haemorrhage (ICH) is a common form of stroke that affects millions of people worldwide. The incidence is associated with a high rate of ...

Uncemented hip arthroplasty and denosumab: increased postoperative dipeptide concentrations and identification of potential new bone turnover biomarkers.

Denosumab is a potent antagonist of RANKL and is widely used to treat severe postmenopausal osteoporosis. Using high-resolution mass spectrometry (HRM...

Artificial Intelligence in Rhinoplasty: Precision or Over-Reliance?

The integration of artificial intelligence (AI) into rhinoplasty has transformed preoperative planning and patient communication by providing highly a...

Diagnosis of early idiopathic pulmonary fibrosis: current status and future perspective.

The standard approach to diagnosing idiopathic pulmonary fibrosis (IPF) includes identifying the usual interstitial pneumonia (UIP) pattern via high r...

Contemporary Prevention and Management of Postoperative Delirium in Cardiac Surgery Patients.

This review examines the prevention and management of postoperative delirium in cardiac surgery patients, a frequent complication linked with signific...

A Comparison of Machine Learning-Based Models and a Simple Clinical Bedside Tool to Predict Morbidity and Mortality After Gastrointestinal Cancer Surgery in the Elderly.

Frailty in the elderly population is associated with increased vulnerability to stressors, including surgical interventions. This study compared machi...

Predicting the risk of postoperative gastrointestinal bleeding in patients with Type A aortic dissection based on an interpretable machine learning model.

BACKGROUND: Gastrointestinal bleeding (GIB) is a common complication following Type A aortic dissection (TAAD) surgery, significantly impacting progno...

Development of a deep-learning algorithm for etiological classification of subarachnoid hemorrhage using non-contrast CT scans.

OBJECTIVES: This study aims to develop a deep learning algorithm for differentiating aneurysmal subarachnoid hemorrhage (aSAH) from non-aneurysmal sub...

The Role of Digital Technologies in Personalized Craniomaxillofacial Surgical Procedures.

Craniomaxillofacial (CMF) surgery addresses complex challenges, balancing aesthetic and functional restoration. Digital technologies, including advanc...

Artificial Intelligence as a Potential Tool for Predicting Surgical Margin Status in Early Breast Cancer Using Mammographic Specimen Images.

: Breast cancer is the most common malignancy among women globally, with an increasing incidence, particularly in younger populations. Achieving compl...

Use of Virtual Reality in the Pediatric Perioperative Setting and for Induction of Anesthesia: Mixed Methods Pilot Feasibility Study.

BACKGROUND: Children commonly experience high levels of anxiety prior to surgery. This distress is associated with postoperative maladaptive behaviors...