Surgery

Utility of augmented reality in endoscopic surgery for stones: European Association of Urology endourology up-to-date review.

PURPOSE OF REVIEW: The development of digital solutions has a direct impact on the modern understanding of the future of urology. Augmented reality is no exception. Specialists use it for intraoperative navigation, which positively impacts procedure metrics, especially in endoscopic surgery for stones. This review aims to determine the chronology of this technology's development and its current tr...

Artificial intelligence-derived electrocardiographic age gap as a predictor of mortality after coronary revascularization: prognostic value and short-term intra-patient variability.

AIMS: The artificial intelligence (AI)-derived electrocardiographic (ECG) age gap-the difference between AI-predicted ECG age and chronological age-is an emerging biomarker of biological ageing linked to mortality. This study assessed its prognostic value for short- and long-term mortality after coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI), addressing model bi...

Machine Learning-based Diagnostic Model Combined with Chinese Natural Language Processing for Surgical Site Infections: Development and Validation.

BACKGROUND: Surgical site infections (SSI) is a major healthcare-associated complication, yet early detection remains challenging. OBJECTIVE: To devel...

Early Prediction of Standing at Discharge in Moderate-to-Severe TBI: A Clinical Machine Learning Model Integrating Modifiable and Nonmodifiable Factors.

OBJECTIVE: To develop and internally validate a machine learning model to predict favorable standing ability at hospital discharge in patients with mo...

Advances in the application of photodynamic diagnosis in Skin Tumors.

Photodynamic Diagnosis (PDD) is a non-invasive imaging technique. It relies on a photosensitizer that, when activated by a specific light source, caus...

Machine Learning of Acoustic Voice Outcomes in Idiopathic Subglottic Stenosis.

OBJECTIVE: There are no objective reliable non-invasive screening tools to identify disease severity in patients with idiopathic subglottic stenosis (...

Identifying patients at risk for short-term adverse events after hip arthroscopy: a machine learning analysis of a national database.

PURPOSE: To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight ...

An algorithm for automated femoral leg length and offset calculations on pelvis radiographs.

INTRODUCTION: Manual measurement of leg length (LL) and offset can be tedious. This study developed an automated algorithm for measuring LL and offset...

Prediction of Ki-67 expression in invasive breast cancer with dual-modality radiomics.

Ki-67 expression, a critical biomarker for tumor aggressiveness and proliferation in invasive breast cancer, is traditionally assessed via invasive bi...

Association of surgical resection with survival in retroperitoneal leiomyosarcoma based on SEER propensity score matching and machine-learning models.

Retroperitoneal leiomyosarcoma (RLS) is a rare and aggressive subtype of soft tissue sarcoma with limited population-level evidence guiding surgical d...

A noninvasive model for predicting intrahepatic venovenous shunts before HVPG measurement: a multiple cohort study.

OBJECTIVES: This study aimed to construct a machine learning (ML) model to facilitate non-invasive identification of moderate-to-severe intrahepatic v...

Human-in-the-loop validation of an artificial intelligence-driven real-time prostatic capsule recognition model for nerve-sparing robot-assisted radical prostatectomy.

BACKGROUND: Nerve-sparing robot-assisted radical prostatectomy (NS-RARP) requires precise prostatic capsule identification to balance oncological cont...

Artificial intelligence-based pathological model for pan-cancer lymph node metastasis detection: a multicentre diagnostic study with retrospective and prospective validation.

BACKGROUND: Accurate detection of lymph node metastasis is crucial for precise tumour staging and treatment planning. Conventional pathological examin...

Cost-effectiveness analysis of artificial intelligence-assisted risk stratification of indeterminate pulmonary nodules.

BACKGROUND: Artificial intelligence-based radiomic approaches have been shown to accurately evaluate indeterminate pulmonary nodules. With the expansi...

Digital Stethoscope-Derived Single-Lead Electrocardiogram and Artificial Intelligence to Detect Low Ejection Fraction: A Multicenter Observational Study.

OBJECTIVES: Identifying patients likely to benefit from an echocardiogram before surgery is prudent in resource-limited settings. Recently, artificial...

Surgical MAchine learning model for predicting Risk of postoperative infecTions in general elective surgery (SMART): A modelling study.

OBJECTIVE: To apply a machine learning (ML) model that we developed and internally validated for predicting postoperative infection likelihood after e...

Evaluation of Otolaryngology Provider Bias in Portal Messaging.

BACKGROUND/OBJECTIVES: Patient messaging portals are widely used in clinical practice and are linked to improved patient outcomes, but they are also a...

Reflectance confocal microscopy in the management of lentigo maligna and lentigo maligna melanoma: a systematic review.

BACKGROUND: Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are difficult to manage because of their subclinical extension and ill-defined mar...

Fully automated, deep learning, cardiac CT-based multimodal network for cardiovascular risk stratification in high-risk perioperative patients.

AIMS: Major adverse cardiac events (MACE) significantly impact perioperative morbidity and mortality. We aimed to develop a fully automated multimodal...

From science fiction to operating room: Representations of surgery and AI in film and their ethical implications.

This paper examines the intricate relationship between surgical practice, artificial intelligence (AI), and science fiction movies, focusing on how im...