Surgery

Radiological staging clinical decision support model for rectal cancer lymph node metastasis detection on MRI.

BACKGROUND: Accurate staging of lymph node metastasis (LNM) is crucial for personalising rectal cancer treatment. Lymph nodes (LNs) are the most common sites of rectal cancer metastasis, and malignant LNs are typically treated with neo-adjuvant radiotherapy or chemoradiotherapy (CRT) to reduce the chance of recurrence and distant metastasis after surgery. Radiological staging criteria, based on LN...

Nomogram and machine learning models for predicting the risk of delirium in ICU patients with NSTEMI.

Delirium is a frequent and clinically consequential complication among patients admitted to the intensive care unit (ICU). Early risk stratification in patients with non-ST-segment elevation myocardial infarction (NSTEMI) remains challenging. We aimed to develop and validate prediction models for ICU delirium in NSTEMI patients using Boruta-based feature selection and machine learning (ML) approac...

Predicting poor wrist function recovery after internal fixation of distal radius fractures: A retrospective study based on multivariate analysis and machine learning models.

This study aimed to identify independent risk factors associated with poor wrist function recovery 6 months after internal fixation of distal radius f...

Morphing median fin enhances untethered tuna-inspired robotic fish's linear acceleration and turning maneuverability.

Median fins in fish-like swimmers critically govern linear acceleration and maneuvering performance, yet their function remains underexplored in untet...

Conversational artificial intelligence in the operating room: an exploratory cross-sectional single-center survey among anesthesiology residents.

BACKGROUND: Conversational artificial intelligence (AI) tools, such as large language models and chat-based systems, are increasingly used by clinicia...

Development and Internal Evaluation of EAST-BMS (East Asian Survival Tool for Bone Metastasis Surgery): A Multinational Machine-learning Survival Prediction Model for Patients Undergoing Surgery for Nonspinal Bone Metastasis in East Asia.

BACKGROUND: Patients undergoing surgery for bone metastases typically have advanced disease, and postoperative survival varies substantially. Accurate...

Prediction and diagnosis of post-stroke epilepsy using artificial intelligence approaches: a systematic review and meta-analysis.

INTRODUCTION: Post-stroke epilepsy (PSE) is a common complication following a stroke and is a major cause of epilepsy in the elderly. Artificial intel...

Machine learning application in the prediction of postoperative delirium among elderly patients: a systematic review and meta-analysis.

PURPOSE: This meta-analysis systematically evaluates machine learning (ML) applications for predicting postoperative delirium (POD) among elderly pati...

Performance comparison between a deep learning model and spine surgeons in detecting cervical spinal cord compression on radiographs.

OBJECTIVE: This study aimed to develop a deep learning (DL) model for the detection of cervical spinal cord compression on cervical radiographs and co...

Postoperative computed tomography segmentation with artificial intelligence for a closed-loop workflow in computer-assisted jaw reconstruction.

Postoperative computed tomography (CT) segmentation provides invaluable information for reconstruction verification, follow-up treatment, education, a...

Enhanced geometry control powered by AI for UAVS with a robotic arm for compensating for disturbances.

Unmanned Aerial Vehicles (UAVs) equipped with robotic manipulators have emerged as a powerful paradigm for advanced aerial manipulation tasks, includi...

Autonomous RCM-less endoscope control: integrating force-based pivoting with deep learning visual servoing.

Robotic endoscope holders improve visual stability, yet enforcing a fixed remote center of motion (RCM) often induces lateral interaction forces due t...

Machine learning in automatic detection of chordoma signature, postoperative residuals, and prognosis of skull base chordomas.

Skull base chordomas are rare, locally invasive tumors that remain a diagnostic and therapeutic challenge. We developed a machine-learning (ML) radiom...

Understanding Blood-Injection-Injury Phobia: Do Not Miss the Point.

Needle and blood-injection-injury phobia is commonly encountered in the perioperative setting. It can significantly disrupt operating room throughput,...

Trajectory planning method for pipeline installation robots based on AS-DTRRT.

Pipeline installation robots install pipelines on both sides of mine roadways using robotic arms; the geometric shape and length of the pipelines affe...

Prediction of Postoperative Complications Following Mandibular Fractures Using Machine Learning.

Postoperative complications in oral and maxillofacial surgery (OMFS), pose a significant challenge to patient recovery. Accurate prediction of such co...

Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics.

Accurate prediction of surgical case duration is essential for reducing operating room overruns and maximising theatre utilisation. Traditional estima...

Resource-Conscious Modeling for Next-Day Discharge Prediction Using Clinical Notes.

Timely discharge prediction is important for surgical unit operations. Using 3,928 postoperative patient notes (32.2% positive), we compared TF-IDF mo...

Kernel Density Estimation of Wearable Signals to Predict Preoperative Cancellation Risk.

Digital health approaches that leverage consumer wearables and machine learning offer scalable means to detect acute illness pre-symptomatically, enab...

MAP-CARE: Enhancing Cross-Lingual Medical Intervention Terms.

Traditional keyword-based or single-language systems are not able to align data from surgical and interventional procedures, especially from non-Engli...