Surgery

Advances in Predicting Postoperative Atrial Fibrillation: A Narrative Review of the Current Literature.

Postoperative atrial fibrillation (POAF) is a common adverse event after cardiac surgery. It is associated with increased risk of both morbidity and mortality. Predictive modalities that stratify patients vulnerable to POAF have demonstrated both poor efficacy and conflicting results on their predictive ability. This narrative review aims to highlight the research on the existing technological POA...

Artificial intelligence in the recognition of stages in live laparoscopic cholecystectomy.

Laparoscopic cholecystectomy is the gold standard for treating symptomatic gallstones. Despite established safety strategies, variability in their adoption leads to inconsistent outcomes. Artificial intelligence (AI) offers potential for real-time recognition of procedural stages, contributing to surgical standardization and safety. A prospective observational study was conducted between February ...

Comment on "Machine learning model for predicting a high comprehensive complication index following rectal cancer surgery".

AI-assisted cryo-dose estimation and tissue injury modeling for assessing side effects in MRI-guided prostate cryoablation: a retrospective study.

Focal therapy offers a middle ground between active surveillance and whole-gland treatment for patients with low- and intermediate-risk prostate ...

Clinical Integration of 3-Dimensional Printing in Shoulder Surgery: Current Applications, Evidence, and Future Directions: A Narrative Review.

» Three-dimensional printing improves shoulder surgery by creating precise anatomical models for better planning and visualization.» Patient-specific ...

Prediction of Symptomatic Radiation Pneumonitis in Lung Cancer Patients: A Radiomics and Dosiomics Machine Learning Approach Using the Prospective Multicenter RTOG 0617 and REQUITE Trials.

PURPOSE: Radiation-induced pneumonitis (RP) is a side effect after thoracic radiation therapy (RT). The ability to predict RP would facilitate treatme...

Predicting Visual Outcomes in Congenital Posterior Lens Opacities: A Deep Learning Model Using Ultra-Widefield Fundus Images.

PURPOSE: To develop and validate a deep learning (DL) model for the automatic segmentation of lens opacity projected shadow (LOPS) on ultra-widefield ...

KRT15 identified by scRNA-Seq and machine learning as stemness regulator and prognostic biomarker in ESCC.

Postoperative recurrence and metastasis in esophageal squamous cell carcinoma (ESCC) are closely associated with cancer stem cells (CSCs), though the ...

The role of artificial intelligence in pre-operative prediction of completeness of cytoreduction for peritoneal surface malignancies: a scoping review.

BACKGROUND: Complete cytoreduction is the most important prognostic factor for patients with peritoneal surface malignancies (PSM) and its prediction ...

Prediction of hemorrhagic transformation after intravenous thrombolysis in acute anterior circulation ischemic stroke through radiomics-based machine learning models.

BACKGROUND: Hemorrhagic transformation (HT) and its associated neurological deterioration remain major concerns that limit decision-making in thrombol...

Normal-resolution vs. super-resolution deep learning reconstruction for diagnosis of functionally significant coronary stenosis using cardiac CT.

BACKGROUND: Super-resolution deep learning reconstruction (SR-DLR) has been developed to reduce image noise and enhance spatial resolution beyond that...

Optimization and External Validation of a Deep Learning Model for Segmentation and Quantification of Traumatic Brain Injury Lesions on Head Computed Tomography.

Current methods for radiological classification in traumatic brain injury (TBI), such as the Marshall and Rotterdam score, provide an incomplete descr...

Intraoperative Ultrasound-Based Displacement Mapping Through Deep Learning.

BACKGROUND AND OBJECTIVES: Brain shift during neurological surgery for brain tumors can be caused by factors such as retraction, resection, and osmoti...

Use of a Novel Intraoperative Neurocognitive Monitoring Task During Awake Craniotomy for Tumor Resection in the Language-Dominant Parietal Lobe.

BACKGROUND AND OBJECTIVES: The identification of eloquent structures in the parietal lobe during awake craniotomy remains challenging, particularly fo...

Development and internal-external validation of a machine learning model to predict the risk for postoperative adverse events in patients with peptic ulcer perforation: a secondary cohort study of the perforated peptic ulcer analyzing project study.

BACKGROUND: Morbidity and mortality rates after surgery in patients with perforated peptic ulcer (PPU) remain high. Although several scoring systems h...

Efficacy and neural mechanisms of a vibrotactile-enhanced, brain-controlled soft robotic glove for upper limb rehabilitation after stroke: a multicentre randomised controlled trial protocol.

INTRODUCTION: Soft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demonstrated potential in facilitating motor recovery a...

Clinical-grade autonomous cytopathology through whole-slide edge tomography.

Cytopathology, often abbreviated as cytology, has a central role in the early detection of cancer, such as cervical, lung and bladder cancers, owing t...

Global research status in the treatment of glaucoma: a systematic bibliometric analysis.

AIM: To present an overview of the research on global glaucoma treatment in the last decade in terms of publication year, journals, countries/regions,...

Hypoglycemia problem-solving ability as a key predictor of severe hypoglycemia: a machine learning approach in adults with type 1 diabetes.

AIMS/INTRODUCTION: Severe hypoglycemia (SH) is a major complication in adults with type 1 diabetes mellitus (T1DM). The multifactorial etiology of T1D...

Artificial intelligence-driven triage and decision-making in trauma systems/settings.

PURPOSE OF REVIEW: Trauma care demands rapid decision-making under uncertainty and time pressure, where maintaining situational awareness becomes chal...