Surgery

Machine learning-based prediction model for postoperative blood transfusion in pediatric patients with Hirschsprung's disease.

BACKGROUND: Children undergoing Hirschsprung's disease (HD) surgery are at risk of postoperative transfusion, which may cause complications and increase resource use. Current decisions are often empirical and lack individualized prediction tools. METHODS: We retrospectively analyzed 889 pediatric patients who underwent HD corrective surgery at a tertiary center (2015-2025). Postoperative transfusi...

Detecting Incisional Surgical Site Infections on Wound Images Through Deep Learning.

IMPORTANCE: Surgical site infections (SSIs) are common postoperative complications, often detected after patients leave the hospital, especially in times of modern fast-track recovery protocols. At-home monitoring through telemedicine can shorten delay to diagnosis. Manual wound image review in telemedicine is time-consuming, shows interobserver variability, and may miss early signs. OBJECTIVE: To...

Convergent binocular stereo: Depth perception for humanoid robot vision.

The design of robotic binocular camera systems has been inspired by human vision, as has their use in humanoid robots. One aspect of this inspiration ...

Investigation of drilling and necrosis zone performance of split point drills in surgical cortical bone drilling.

The surgical bone drilling process is unavoidable in orthopedic, traumatological and dental applications for screw, plate and implant placement proced...

RNA biosensors in oncology: Mechanisms, Cancer-specific applications, and a Hallmark-aligned clinical roadmap.

Cancer diagnosis continues to rely on invasive tissue sampling and static molecular assessments that cannot reflect the real time RNA alterations driv...

Clinical significance of lncRNA-miRNA axes in ischemic stroke: Diagnostic value, prognostic relevance, and therapeutic potential.

Ischemic stroke and subsequent reperfusion injury are major causes of mortality and long-term neurological disability, driven by complex mechanisms of...

Deep Learning-Based Classification of NIFTP and Invasive Encapsulated Follicular Variant of Papillary Thyroid Carcinoma Using Gross Pathology Images.

Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and invasive encapsulated follicular variant of papillary thyroi...

Explainable artificial intelligence reveals key surgical parameters in robot-assisted and open radical prostatectomy.

Preoperative risk stratification for radical prostatectomy is crucial, yet predicting the wide range of postoperative outcomes remains a significant c...

The metabolic-inflammatory axis in chronic heart failure: integrating the NLR and TyG index for recent-onset atrial fibrillation prediction via machine learning and mediation analysis.

INTRODUCTION: Recent-onset atrial fibrillation (AF) is a common complication of chronic heart failure (CHF), potentially involving both inflammatory a...

Machine Learning Modeling for Predicting Mortality in Pediatric Patients Undergoing Elective Noncardiac Surgery: Comparison to a Regression Model.

BACKGROUND: Perioperative mortality in children is relatively rare; however, accurate preoperative risk stratification is critical, as it enables anti...

Research progress in the clinical application of AI in strabismus.

PURPOSE: Strabismus diagnosis and management remain subjective due to variable measurement techniques and lack of standardized surgical criteria. Arti...

A Rasch-based analysis comparing the performance of updated multimodal large language models and surgeons on the Japanese surgical specialist examination.

PURPOSE: To compare four multimodal large language models (LLMs) with surgeons on the 2023 Japanese Surgical Specialist Examination using item-level s...

Robot-assisted Computer-Implant surgery : A comprehensive review of system architecture, clinical accuracy, and emerging technologies.

Advances in intelligent technologies have endowed robots with unprecedented advantages in medical applications. In dental implant surgery, the growing...

AMR-VSF: an adaptive memory correction framework for robust 3D CT aorta segmentation.

PURPOSE: Accurate 3D aortic segmentation in CT images is vital for cardiovascular disease diagnosis, surgical planning, and intraoperative navigation....

Potential of Remote Patient Monitoring in Perioperative Care: A Narrative Review.

Remote patient monitoring is moving closer to routine implementation and has the potential to become an important component of perioperative care: wit...

Machine Learning Models for Predicting Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement: A Scoping Review.

Permanent pacemaker (PPM) implantation has been reported in up to 26% of patients undergoing transcatheter aortic valve replacement (TAVR). Machine le...

Diagnosis of Clinically Significant Prostate Cancer in Multiparametric MRI with Pseudo-Localization of Suspected Lesion.

To develop a two-stage diagnostic framework using pseudo-localization for patient-level diagnosis of clinically significant prostate cancer (csPCa) on...

Prediction of Lymph Node Metastasis in Early Gastric Cancer Using Foundation Model Ensembles and Patch-Based Histopathological Interpretation.

PURPOSE: Accurate prediction of lymph node metastasis (LNM) remains challenging in early gastric cancer (EGC), particularly when determining the need ...

Improving care for distal hypospadias: recent studies provide a blueprint for improved diagnostics and optimized operative outcomes.

PURPOSE OF REVIEW: Recent clinical studies provide key insights into our current approach to the management of distal hypospadias. This common conditi...

Brain cone-beam CT image quality improvement using a deep-learning-based denoising method: a multicenter retrospective study.

PURPOSE: Deep learning (DL) denoising may improve cone-beam CT (CBCT) image quality for point-of-care stroke assessment in the interventional suite. T...