Surgery

Nurse-Led Large Language Model Chatbot for Predicting and Preventing Complications After Coronary Artery Bypass Grafting: Protocol for a Randomized Controlled Trial.

BACKGROUND: Thirty-day unplanned readmission following coronary artery bypass grafting (CABG) affects 10%-20% of patients and is a key quality indicator, particularly in low- and middle-income countries (LMICs) where access to cardiac rehabilitation is limited. Existing risk models are static, lack real-time engagement, and no validated large language model (LLM)-based clinical decision support (C...

Nonlinear neurodynamics of N2 sleep EEG predict outcomes of anterior nucleus of the thalamus deep brain stimulation in epilepsy: A pilot study.

OBJECTIVE: Anterior nucleus of the thalamus deep brain stimulation (ANT-DBS) is an effective therapeutic option for drug-resistant epilepsy (DRE); however, substantial inter-individual variability in treatment response limits its clinical optimization. This study aimed to develop an objective and explainable preoperative prediction model for ANT-DBS outcomes using nonlinear dynamical features deri...

Quality and Readability of AI Chatbot Responses to Frequently Asked Questions from Patients Undergoing Progressive Collapsing Foot Deformity Surgery: A Comparative Study of ChatGPT, Perplexity, and Gemini.

BACKGROUND: Patients increasingly turn to AI chatbots for medical information, including before complex orthopaedic procedures such as progressive col...

What predicts postoperative opioid prescribing and consumption? A statewide analysis of surgical quality registry data.

OBJECTIVE: Tailoring postoperative opioid recommendations to patient needs requires nuanced understanding of factors contributing to post-discharge op...

Explainable Machine Learning for Perioperative Risk Stratification of Radiographic Adjacent Segment Degeneration After Short-Segment Lumbar Fusion.

STUDY DESIGN: Retrospective Cohort Study. OBJECTIVES: To develop and externally validate an explainable machine-learning framework for perioperative r...

UCtracker: A Deep Learning-Based DNA Methylation Model for Noninvasive Diagnosis and Recurrence Surveillance of Urothelial Carcinoma in a Prospective Study.

Noninvasive diagnosis and longitudinal surveillance of urothelial carcinoma (UC) remain clinically challenging. Here, we developed and prospectively v...

Assessment methods for surgeons' ergonomics in the operating room: a scoping review.

BACKGROUND: Ergonomics is essential for ensuring safe, high-quality surgical care. However, existing studies vary widely in their clinical settings, t...

Global research trends in robotic applications in cosmetic dermatology: a bibliometric analysis.

Robotic technologies are increasingly being integrated into cosmetic dermatology; however, the scientific development of this field has not been compr...

Functional outcome prediction after traumatic cervical spinal cord injury using ensemble machine learning: a three‑center validation study.

BACKGROUND: Traumatic cervical spinal cord injury (TCSCI) often causes severe neurological dysfunction. Accurate prediction of functional recovery is ...

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review.

PURPOSE: To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting kn...

Deep-Learning-Based Assessment of Postoperative Nasolabial Morphology in Unilateral Cleft Lip Repair.

BACKGROUND: Objective assessment of postoperative facial appearance following unilateral cleft lip and palate (UCLP) repair remains limited by subject...

The digital scalpel: navigating the future of surgical innovation.

BACKGROUND: Artificial intelligence is entering surgical practice not as an extension of the surgeon's hand, eyes, or dexterity, but of surgical judgm...

Personalized Prediction of Acute and Chronic Postsurgical Pain - the role of Multidomain Biosignatures, Machine Learning-Based Integration, and Standardized Outcome Definitions.

PURPOSE OF THE REVIEW: Acute postsurgical pain (APSP) and chronic postsurgical pain (CPSP) remain prevalent and insufficiently resolved challenges in ...

Construction and Validation of a Risk Prediction Model for Acute Pulmonary Hemorrhage in Very Low Birthweight Infants.

OBJECTIVE: Very low birthweight infants (VLBWIs) are at high risk of pulmonary hemorrhage, yet practical and effective early prediction tools remain l...

DAFNet: A multi-modal deep learning model based on whole-lung CT for the automated prediction of the air space spread of lung adenocarcinoma.

Spread through air spaces (STAS) is a characteristic invasive pattern of lung adenocarcinoma (LUAD), which is associated with a high recurrence rate a...

Tertiary Lymphoid Structures as Predictors of Recurrence in Colorectal Cancer: Development and Validation of a Machine Learning-Based Scoring Model.

BACKGROUND: Tertiary lymphoid structures (TLS) are prognostic immune aggregates in the tumor microenvironment, but the value of location-specific TLS ...

Real-Time Anatomy Recognition During Single-Port Retroperitoneal Surgery: A Prospective Comparison Between AI and Operating Surgeon.

BACKGROUND: Real-time anatomical recognition during robot-assisted surgery has the potential to enrich intraoperative decision-making. We made the fir...

Physician-Supervised ChatGPT-Assisted Versus Physician-Led Informed Consent for Reducing Preoperative Anxiety: A Randomized Controlled Trial.

PURPOSE: To evaluate whether ChatGPT-assisted informed consent (IC) is noninferior to conventional physician-led IC in reducing preoperative anxiety (...

Exploratory machine learning-based early post-treatment assessment of willingness to reuse rubber dam isolation after microscopic root canal treatment.

ObjectiveTo explore factors associated with willingness to reuse rubber dam isolation after microscopic root canal treatment and develop an explorator...

A multimodal prediction model for brain hematoma expansion based on deep neural network with transformer-driven collaborative attention fusion.

Hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (ICH) is strongly associated with death and disability, so accurate earl...