Surgery

Toward a future role for liver biopsy in HCC: literature evidence and survey-based perspectives from Korean experts.

The role of liver biopsy in hepatocellular carcinoma (HCC) is being re-evaluated in the era of precision oncology and biomarker-driven systemic therapy. Although histopathological examination remains the diagnostic gold standard, HCC is unique among solid tumors in that accurate non-invasive imaging criteria allow diagnosis without routine biopsy in selected clinical settings. However, increasing ...

PCa Detection in PI-RADS 4 and 5 Lesions: Comparison of [68Ga]Ga-PSMA-11 PET/CT-Guided Robot-Assisted Biopsy Versus mpMRI Cognitive-Fusion TRUS-Guided Prostate Biopsy.

Lesions with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 4 or greater on multiparametric MRI (mpMRI) indicate a high likelihood of prostate cancer (PCa), and guidelines recommend a targeted biopsy. We aimed to compare the diagnostic performance of robotic arm-assisted [68Ga]Ga-PSMA-11 PET/CT-guided prostate biopsy (PGPB) with mpMRI-directed cognitive-fusion transrectal ultrasou...

Patient Perceptions Across a Fixed Sequence of Physician Attire and Surgical-Context Images in Urology: An Image-Based Cross-Sectional Survey.

BACKGROUND: Physician attire is associated with patient trust and confidence, yet it has rarely been examined in urology or in the surgical context in...

Radiomics and artificial intelligence in pituitary adenomas (PitNETs): from imaging biomarkers to clinical translation.

Pituitary neuroendocrine tumors (PitNETs) are common intracranial neoplasms with heterogeneous hormonal activity, invasiveness, and treatment response...

Predicting Craniospinal Surgery in Pediatric Achondroplasia: Benchmarking Statistical Inference and Explainable AI Under Rare-Disease Constraints.

PURPOSE: To develop a framework that benchmarks penalized statistical inference against explainable artificial intelligence (XAI) methods for predicti...

An Exosomal Signature for Preoperative Detection of Occult Liver Metastasis in Pancreatic Cancer.

IMPORTANCE: Early liver metastasis (early-LiM) after pancreatectomy represents an aggressive biological phenotype of pancreatic ductal adenocarcinoma ...

Automatic Kidney Image Segmentation During Robot-Assisted Partial Nephrectomy Using a Deep Learning Model Based on a Multiannotator Dataset: Model Development and Validation Study.

BACKGROUND: Augmented reality (AR) has emerged as a promising tool to enhance surgical precision during robot-assisted partial nephrectomy (RAPN), par...

Harmonizing complexity and efficiency: Helix Fusion HarmonyNet's breakthrough in EEG-based postoperative delirium recognition.

Postoperative delirium (POD) is a common perioperative complication involving central nervous system dysfunction, particularly among critically ill an...

Large language models in the vertical integration of spine surgery workflow: a scoping review.

PURPOSE: To evaluate current evidence regarding the clinical reliability and reasoning capabilities of Large Language Models (LLMs) and Multimodal Lar...

Artificial Intelligence-predicted Outcomes of Breast Reconstruction: Progress, Pitfalls, and Path Forward.

BACKGROUND: Artificial intelligence (AI) is increasingly being applied across medical disciplines to enhance clinical decision-making. However, its us...

Embodied artificial intelligence in robotic orthopaedic surgery: from intelligent assistance to adaptive surgical autonomy.

Despite remarkable advances in robotic orthopaedic surgery over the past three decades, current commercial platforms remain precision-assistance techn...

Multicenter machine learning model using clinical and radiomic features for prediction of postoperative residual status in meningioma.

OBJECTIVE: Gross-total resection is the primary surgical objective in meningioma management; however, predicting resectability preoperatively remains ...

Robotic sorting and artificial intelligence in material recovery facilities: a review of published research and expert perspectives.

Material Recovery Facilities (MRFs) are essential to municipal recycling infrastructure, but face difficulties in sorting due to the growing complexit...

Multiparametric MRI-Based Ensemble Deep Learning for Preoperative Classification of Pituitary Neuroendocrine Tumor Subtypes.

RATIONALE AND OBJECTIVES: Pituitary neuroendocrine tumors (PitNETs) exhibit diverse biological behavior requiring accurate subtyping to guide treatmen...

Development and external validation of a contrastive learning foundation model for ECG-based prediction of cardiovascular diseases and outcomes.

BACKGROUND: Automated electrocardiogram (ECG) assessment tools to assist clinicians in diagnosis have improved substantially over the past decade; how...

A Clinically Aligned Two-Stage Machine Learning Framework for Predicting Hungry Bone Syndrome After Parathyroidectomy.

BACKGROUND: Hungry bone syndrome (HBS) is a frequent and clinically significant complication following parathyroidectomy (PTX) in patients with second...

Development and Clinical Utility of Machine Learning Models for Prediction of Same-Day Discharge in Outpatient Hip and Knee Replacement: A Prognostic Study.

BACKGROUND: Hip and knee replacement are common procedures with an increasing focus on same-day surgery. However, capacity constraints limit the numbe...

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intellige...

Artificial intelligence as a clinical capability enhancer in minimally invasive gynecologic surgery.

Development and Validation of an Interpretable Machine Learning Model for Predicting ICU-Acquired Weakness in Postoperative Patients.

BACKGROUND: ICU-acquired weakness (ICU-AW) is a common and debilitating complication among critically ill patients, particularly those undergoing majo...