Surgery

Development and mixed-methods evaluation of the Prehabilitation for Facial Feminization Surgery (PREFACE) Program.

BACKGROUND: To strengthen preoperative preparation and improve clinical outcomes, a multimedia prehabilitation program was created for patients undergoing facial feminization surgery (FFS). This study evaluates the program and its impact on clinical outcomes. METHODS: PREFACE includes five video modules, a guidebook, and a mobile application covering surgical information, preoperative preparation,...

Compositionality and systematicity emerge from iterated learning in deep linear networks.

Humans have a remarkable ability to systematically generalize-reasoning about new situations by combining aspects of previous experiences. Language provides one of the primary examples of this ability and modern machine learning has drawn much inspiration from linguistics. A recent example is iterated learning, a procedure where generations of networks learn from the output of earlier learners. Th...

Predicting postoperative atrial fibrillation after cardiac surgery using machine learning.

BACKGROUND: Postoperative atrial fibrillation (POAF) is a frequent complication after cardiac surgery that is associated with increased morbidity. How...

Diuretic Ultrasound Evaluation of Surgical Necessity in Pediatric Ureteropelvic Junction Obstruction.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning (ML) model using diuretic ultrasonography to predict the neces...

Global Trends in Postoperative Sepsis After Pancreatoduodenectomy: A Bibliometric Analysis.

INTRODUCTION: Postoperative sepsis after pancreatoduodenectomy (PSPD) remains a major determinant of morbidity and mortality. Although extensive clini...

Medical AI, inductive risk and the communication of uncertainty: the case of disorders of consciousness.

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. ...

Predicting Protracted Recovery and Long-Term Loss of Independence after Major Surgery in Veterans.

IMPORTANCE: Surgery often has lasting impacts on quality of life, which requires outcome measurement beyond 30 days. Even when long-term outcomes are ...

Artificial Intelligence in the Trauma Bay: A Pilot Comparison With Surgical Trainees.

BackgroundLarge language models (LLMs) have demonstrated strong performance on general medical knowledge assessments; however, their accuracy within h...

Can Artificial Intelligence Replicate Clinical Judgment in Aesthetic Surgery? A Comparison of ChatGPT and Plastic Surgeons' Recommendations.

BACKGROUND: Since the emergence of the Chat Generative Pre-Trained Transformer (ChatGPT), artificial intelligence (AI) has change how medical informat...

Artificial Intelligence-Based Prognostic Models for Postoperative Outcomes in Vitreoretinal Surgery: A Systematic Review and Meta-Analysis.

TOPIC: This review evaluated the performance of artificial intelligence (AI) models for predicting outcomes after vitreoretinal surgery compared with ...

AI-enabled digital wound monitoring after cardiac surgery: a randomised controlled feasibility, safety, and acceptability trial.

BACKGROUND: Surgical site infection after cardiac surgery is a common cause of morbidity and unplanned healthcare use, with most infections developing...

Development and validation of a risk stratification model for sarcopenia in patients with chronic lung disease: a cross-sectional study based on CHARLS data.

OBJECTIVE: The aim of this study was to develop a machine learning-based stratification model to identify high-risk individuals for sarcopenia among p...

Machine learning predicts postoperative mortality in a Latin American cardiovascular surgery multicenter cohort: Toward precision risk stratification.

OBJECTIVE: A total of 28% of global cardiac surgeries are performed in Latin America; however, surgeons there are faced with many preventable deaths, ...

[AI-based surgical planning of adult spinal deformities : Analysis of an AI-based tool for correction planning and execution employing patient-specific contoured rods].

BACKGROUND: Optimal alignment correction can potentially lower the high complication rates of adult scoliosis surgeries. AI tools can help make the an...

Breaking the Black Box: Interpretable AI Achieves Superior Hemorrhage Detection with the Compensatory Reserve Measurement.

Hemorrhage remains the leading cause of preventable trauma death, with traditional vital signs failing to detect blood loss until 25-30% volume deplet...

Physician Perspectives on ChatGPT-4o as a Patient Resource for Abdominal Cancer Surgeries: Cross-Sectional Survey.

BACKGROUND: Artificial intelligence (AI) models are being increasingly integrated into clinical care. Moreover, the availability of publicly accessibl...

Noninvasive molecular subtyping of breast cancer using multimodal ultrasound spatiotemporal transformer.

Molecular subtyping is essential for guiding systemic therapy in breast cancer but currently requires invasive biopsy. Conventional B-mode ultrasound ...

Explainable and visualizable machine learning model development and validation for 5-year postoperative survival prediction in prostate cancer patients aged ≥ 65 years.

BACKGROUND: Machine Learning (ML) models have achieved outstanding performance in predicting post-surgical survival. However, the "black-box" nature o...

Interpretable machine learning for postoperative nausea and vomiting prediction in elderly orthopedic patients: a comparative study.

BACKGROUND: Postoperative nausea and vomiting (PONV) prolongs hospitalization and reduces patient satisfaction. Identifying high-risk elderly patients...

Imaging Biomarkers for Early Differentiation of Candida and Aspergillus Endogenous Fungal Endophthalmitis: Multicenter Optical Coherence Tomography-Based Analysis.

PURPOSE: Endogenous fungal endophthalmitis (EFE) is a rare, sight-threatening intraocular infection with heterogeneous clinical presentations. Candida...